2008
Rodrigues, Miguel R D; Perez-Cruz, Fernando; Verdu, Sergio
Multiple-Input Multiple-Output Gaussian Channels: Optimal Covariance for Non-Gaussian Inputs Artículo en actas
En: 2008 IEEE Information Theory Workshop, pp. 445–449, IEEE, Porto, 2008, ISBN: 978-1-4244-2269-2.
Resumen | Enlaces | BibTeX | Etiquetas: Binary phase shift keying, covariance matrices, Covariance matrix, deterministic MIMO Gaussian channel, fixed-point equation, Gaussian channels, Gaussian noise, Information rates, intersymbol interference, least mean squares methods, Magnetic recording, mercury-waterfilling power allocation policy, MIMO, MIMO communication, minimum mean-squared error, MMSE, MMSE matrix, multiple-input multiple-output system, Multiple-Input Multiple-Output Systems, Mutual information, Optimal Input Covariance, Optimization, Telecommunications
@inproceedings{Rodrigues2008,
title = {Multiple-Input Multiple-Output Gaussian Channels: Optimal Covariance for Non-Gaussian Inputs},
author = {Miguel R D Rodrigues and Fernando Perez-Cruz and Sergio Verdu},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4578704},
isbn = {978-1-4244-2269-2},
year = {2008},
date = {2008-01-01},
booktitle = {2008 IEEE Information Theory Workshop},
pages = {445--449},
publisher = {IEEE},
address = {Porto},
abstract = {We investigate the input covariance that maximizes the mutual information of deterministic multiple-input multipleo-utput (MIMO) Gaussian channels with arbitrary (not necessarily Gaussian) input distributions, by capitalizing on the relationship between the gradient of the mutual information and the minimum mean-squared error (MMSE) matrix. We show that the optimal input covariance satisfies a simple fixed-point equation involving key system quantities, including the MMSE matrix. We also specialize the form of the optimal input covariance to the asymptotic regimes of low and high snr. We demonstrate that in the low-snr regime the optimal covariance fully correlates the inputs to better combat noise. In contrast, in the high-snr regime the optimal covariance is diagonal with diagonal elements obeying the generalized mercury/waterfilling power allocation policy. Numerical results illustrate that covariance optimization may lead to significant gains with respect to conventional strategies based on channel diagonalization followed by mercury/waterfilling or waterfilling power allocation, particularly in the regimes of medium and high snr.},
keywords = {Binary phase shift keying, covariance matrices, Covariance matrix, deterministic MIMO Gaussian channel, fixed-point equation, Gaussian channels, Gaussian noise, Information rates, intersymbol interference, least mean squares methods, Magnetic recording, mercury-waterfilling power allocation policy, MIMO, MIMO communication, minimum mean-squared error, MMSE, MMSE matrix, multiple-input multiple-output system, Multiple-Input Multiple-Output Systems, Mutual information, Optimal Input Covariance, Optimization, Telecommunications},
pubstate = {published},
tppubtype = {inproceedings}
}
We investigate the input covariance that maximizes the mutual information of deterministic multiple-input multipleo-utput (MIMO) Gaussian channels with arbitrary (not necessarily Gaussian) input distributions, by capitalizing on the relationship between the gradient of the mutual information and the minimum mean-squared error (MMSE) matrix. We show that the optimal input covariance satisfies a simple fixed-point equation involving key system quantities, including the MMSE matrix. We also specialize the form of the optimal input covariance to the asymptotic regimes of low and high snr. We demonstrate that in the low-snr regime the optimal covariance fully correlates the inputs to better combat noise. In contrast, in the high-snr regime the optimal covariance is diagonal with diagonal elements obeying the generalized mercury/waterfilling power allocation policy. Numerical results illustrate that covariance optimization may lead to significant gains with respect to conventional strategies based on channel diagonalization followed by mercury/waterfilling or waterfilling power allocation, particularly in the regimes of medium and high snr.
Vazquez, Manuel A; Miguez, Joaquin
A Per-Survivor Processing Algorithm for Maximum Likelihood Equalization of MIMO Channels with Unknown Order Artículo en actas
En: 2008 International ITG Workshop on Smart Antennas, pp. 387–391, IEEE, Vienna, 2008, ISBN: 978-1-4244-1756-8.
Resumen | Enlaces | BibTeX | Etiquetas: Channel estimation, channel impulse response, computational complexity, Computer science education, Computer Simulation, Degradation, Frequency, frequency-selective multiple-input multiple-output, maximum likelihood detection, maximum likelihood equalization, maximum likelihood estimation, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO channels, MIMO communication, per-survivor processing algorithm, time-selective channels, Transmitting antennas
@inproceedings{Vazquez2008a,
title = {A Per-Survivor Processing Algorithm for Maximum Likelihood Equalization of MIMO Channels with Unknown Order},
author = {Manuel A Vazquez and Joaquin Miguez},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4475587},
isbn = {978-1-4244-1756-8},
year = {2008},
date = {2008-01-01},
booktitle = {2008 International ITG Workshop on Smart Antennas},
pages = {387--391},
publisher = {IEEE},
address = {Vienna},
abstract = {In the equalization of frequency-selective multiple-input multiple-output (MIMO) channels it is usually assumed that the length of the channel impulse response (CIR), also referred to as the channel order, is known. However, this is not true in most practical situations and, in order to avoid the serious performance degradation that occurs when the CIR length is underestimated, a channel with "more than enough" taps is usually considered. This possibly means overestimating the channel order, and is not desirable since the computational complexity of maximum likelihood sequence detection (MLSD) in frequency-selective channels grows exponentially with the channel order. In addition to that, the higher the channel order considered, the more the number of channel coefficients that need to be estimated from the same set of observations. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including its order. The proposed technique is based on the per survivor processing (PSP) methodology, it admits both blind and semiblind implementations, depending on the availability of pilot data, and is designed to work with time-selective channels. Besides the analytical derivation of the algorithm, we provide computer simulation results that illustrate the effectiveness of the resulting receiver.},
keywords = {Channel estimation, channel impulse response, computational complexity, Computer science education, Computer Simulation, Degradation, Frequency, frequency-selective multiple-input multiple-output, maximum likelihood detection, maximum likelihood equalization, maximum likelihood estimation, maximum likelihood sequence detection, maximum likelihood sequence estimation, MIMO, MIMO channels, MIMO communication, per-survivor processing algorithm, time-selective channels, Transmitting antennas},
pubstate = {published},
tppubtype = {inproceedings}
}
In the equalization of frequency-selective multiple-input multiple-output (MIMO) channels it is usually assumed that the length of the channel impulse response (CIR), also referred to as the channel order, is known. However, this is not true in most practical situations and, in order to avoid the serious performance degradation that occurs when the CIR length is underestimated, a channel with "more than enough" taps is usually considered. This possibly means overestimating the channel order, and is not desirable since the computational complexity of maximum likelihood sequence detection (MLSD) in frequency-selective channels grows exponentially with the channel order. In addition to that, the higher the channel order considered, the more the number of channel coefficients that need to be estimated from the same set of observations. In this paper, we introduce an algorithm for MLSD that incorporates the full estimation of the MIMO CIR parameters, including its order. The proposed technique is based on the per survivor processing (PSP) methodology, it admits both blind and semiblind implementations, depending on the availability of pilot data, and is designed to work with time-selective channels. Besides the analytical derivation of the algorithm, we provide computer simulation results that illustrate the effectiveness of the resulting receiver.
Leiva-Murillo, Jose M; Artés-Rodríguez, Antonio
Algorithms for Gaussian Bandwidth Selection in Kernel Density Estimators Artículo en actas
En: NIPS 2008, Workshop on Optimization for Machine Learning Vancouver, Vancouver, 2008.
Resumen | Enlaces | BibTeX | Etiquetas:
@inproceedings{Leiva-Murillo2008a,
title = {Algorithms for Gaussian Bandwidth Selection in Kernel Density Estimators},
author = {Jose M Leiva-Murillo and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://www.researchgate.net/publication/228859873_Algorithms_for_gaussian_bandwidth_selection_in_kernel_density_estimators},
year = {2008},
date = {2008-01-01},
booktitle = {NIPS 2008, Workshop on Optimization for Machine Learning Vancouver},
address = {Vancouver},
abstract = {In this paper we study the classical statistical problem of choos-ing an appropriate bandwidth for Kernel Density Estimators. For the special case of Gaussian kernel, two algorithms are proposed for the spherical covariance matrix and for the general case, respec-tively. These methods avoid the unsatisfactory procedure of tuning the bandwidth while evaluating the likelihood, which is impractical with multivariate data in the general case. The convergence con-ditions are provided together with the algorithms proposed. We measure the accuracy of the models obtained by a set of classifica-tion experiments.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we study the classical statistical problem of choos-ing an appropriate bandwidth for Kernel Density Estimators. For the special case of Gaussian kernel, two algorithms are proposed for the spherical covariance matrix and for the general case, respec-tively. These methods avoid the unsatisfactory procedure of tuning the bandwidth while evaluating the likelihood, which is impractical with multivariate data in the general case. The convergence con-ditions are provided together with the algorithms proposed. We measure the accuracy of the models obtained by a set of classifica-tion experiments.
de-Prado-Cumplido, Mario Mario; Artés-Rodríguez, Antonio
SVM Discovery of Causation Direction by Machine Learning Techniques Artículo en actas
En: NIPS’08, Workshop on Causality, Vancouver, 2008.
BibTeX | Etiquetas:
@inproceedings{Mariode-Prado-Cumplido2008,
title = {SVM Discovery of Causation Direction by Machine Learning Techniques},
author = {Mario Mario de-Prado-Cumplido and Antonio Art\'{e}s-Rodr\'{i}guez},
year = {2008},
date = {2008-01-01},
booktitle = {NIPS’08, Workshop on Causality},
address = {Vancouver},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Ruiz, Manuel Martinez; Artés-Rodríguez, Antonio; Sabatini, R
Progressive Still Image Transmission over a Tactical Data Link Network Artículo en actas
En: RTO 2008 Information Systems Technology Panel (IST) Symposium, Praga, 2008.
@inproceedings{MartinezRuiz2008,
title = {Progressive Still Image Transmission over a Tactical Data Link Network},
author = {Manuel Martinez Ruiz and Antonio Art\'{e}s-Rodr\'{i}guez and R Sabatini},
year = {2008},
date = {2008-01-01},
booktitle = {RTO 2008 Information Systems Technology Panel (IST) Symposium},
address = {Praga},
abstract = {Future military communications will be required to provide higher data capacity and wideband in real time, greater flexibility, reliability, robustness and seamless networking capabilities. The next generation of communication systems and standards should be able to outperform in a littoral combat environment with a high density of civilian emissions and “ad-hoc” spot jammers. In this operational context it is extremely important to ensure the proper performance of the information grid and to provide not all the available but only the required information in real time either by broadcasting or upon demand, with the best possible “quality of service”. Existing tactical data link systems and standards have being designed to convey mainly textual information such as surveillance and identification data, electronic warfare parameters, aircraft control information, coded voice. The future tactical data link systems and standards should take into consideration the multimedia nature of most of the dispersed and “fuzzy” information available in the battlefield to correlate the ISR components in a way to better contribute to the Network Centric Operations. For this to be accomplished new wideband coalition waveforms should be developed and new coding and image compression standards should be taken into account, such as MPEG-7 (Multimedia Content Description Interface), MPEG-21, JPEG2000 and many others. In the meantime it is important to find new applications for the current tactical data links in order to better exploit their capabilities and to overcome or minimize their limitations.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Future military communications will be required to provide higher data capacity and wideband in real time, greater flexibility, reliability, robustness and seamless networking capabilities. The next generation of communication systems and standards should be able to outperform in a littoral combat environment with a high density of civilian emissions and “ad-hoc” spot jammers. In this operational context it is extremely important to ensure the proper performance of the information grid and to provide not all the available but only the required information in real time either by broadcasting or upon demand, with the best possible “quality of service”. Existing tactical data link systems and standards have being designed to convey mainly textual information such as surveillance and identification data, electronic warfare parameters, aircraft control information, coded voice. The future tactical data link systems and standards should take into consideration the multimedia nature of most of the dispersed and “fuzzy” information available in the battlefield to correlate the ISR components in a way to better contribute to the Network Centric Operations. For this to be accomplished new wideband coalition waveforms should be developed and new coding and image compression standards should be taken into account, such as MPEG-7 (Multimedia Content Description Interface), MPEG-21, JPEG2000 and many others. In the meantime it is important to find new applications for the current tactical data links in order to better exploit their capabilities and to overcome or minimize their limitations.
Bravo-Santos, Ángel M
Multireception Systems in Mobile Environments Artículo en actas
En: 2008 International Workshop on Advances in Communications, Victoria BC, 2008.
BibTeX | Etiquetas:
@inproceedings{Bravo-Santos2008,
title = {Multireception Systems in Mobile Environments},
author = {\'{A}ngel M Bravo-Santos},
year = {2008},
date = {2008-01-01},
booktitle = {2008 International Workshop on Advances in Communications},
address = {Victoria BC},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Plata-Chaves, Jorge; Lázaro, Marcelino; Artés-Rodríguez, Antonio
Decentralized Detection in a Dense Wireless Sensor Network with Correlated Observations Artículo en actas
En: International Workshop on Information Theory for Sensor Networks (WITS 2008), Santorini, 2008.
@inproceedings{Plata-Chaves2008,
title = {Decentralized Detection in a Dense Wireless Sensor Network with Correlated Observations},
author = {Jorge Plata-Chaves and Marcelino L\'{a}zaro and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://www.dcc.fc.up.pt/wits08/wits-advance-program.pdf},
year = {2008},
date = {2008-01-01},
booktitle = {International Workshop on Information Theory for Sensor Networks (WITS 2008)},
address = {Santorini},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Santiago-Mozos, Ricardo; Fernandez-Lorenzana, R; Perez-Cruz, Fernando; Artés-Rodríguez, Antonio
On the Uncertainty in Sequential Hypothesis Testing Artículo en actas
En: 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 1223–1226, IEEE, Paris, 2008, ISBN: 978-1-4244-2002-5.
Resumen | Enlaces | BibTeX | Etiquetas: binary hypothesis test, Biomedical imaging, Detectors, H infinity control, likelihood ratio, Medical diagnostic imaging, medical image application, medical image processing, Medical tests, patient diagnosis, Probability, Random variables, Sequential analysis, sequential hypothesis testing, sequential probability ratio test, Signal processing, Testing, tuberculosis diagnosis, Uncertainty
@inproceedings{Santiago-Mozos2008,
title = {On the Uncertainty in Sequential Hypothesis Testing},
author = {Ricardo Santiago-Mozos and R Fernandez-Lorenzana and Fernando Perez-Cruz and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4541223},
isbn = {978-1-4244-2002-5},
year = {2008},
date = {2008-01-01},
booktitle = {2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro},
pages = {1223--1226},
publisher = {IEEE},
address = {Paris},
abstract = {We consider the problem of sequential hypothesis testing when the exact pdfs are not known but instead a set of iid samples are used to describe the hypotheses. We modify the classical test by introducing a likelihood ratio interval which accommodates the uncertainty in the pdfs. The test finishes when the whole likelihood ratio interval crosses one of the thresholds and reduces to the classical test as the number of samples to describe the hypotheses tend to infinity. We illustrate the performance of this test in a medical image application related to tuberculosis diagnosis. We show in this example how the test confidence level can be accurately determined.},
keywords = {binary hypothesis test, Biomedical imaging, Detectors, H infinity control, likelihood ratio, Medical diagnostic imaging, medical image application, medical image processing, Medical tests, patient diagnosis, Probability, Random variables, Sequential analysis, sequential hypothesis testing, sequential probability ratio test, Signal processing, Testing, tuberculosis diagnosis, Uncertainty},
pubstate = {published},
tppubtype = {inproceedings}
}
We consider the problem of sequential hypothesis testing when the exact pdfs are not known but instead a set of iid samples are used to describe the hypotheses. We modify the classical test by introducing a likelihood ratio interval which accommodates the uncertainty in the pdfs. The test finishes when the whole likelihood ratio interval crosses one of the thresholds and reduces to the classical test as the number of samples to describe the hypotheses tend to infinity. We illustrate the performance of this test in a medical image application related to tuberculosis diagnosis. We show in this example how the test confidence level can be accurately determined.
Vila-Forcen, J E; Artés-Rodríguez, Antonio; Garcia-Frias, J
Compressive Sensing Detection of Stochastic Signals Artículo en actas
En: 2008 42nd Annual Conference on Information Sciences and Systems, pp. 956–960, IEEE, Princeton, 2008, ISBN: 978-1-4244-2246-3.
Resumen | Enlaces | BibTeX | Etiquetas: Additive white noise, AWGN, compressive sensing detection, dimensionality reduction techniques, Distortion measurement, Gaussian noise, matrix algebra, Mutual information, optimized projections, projection matrix, signal detection, Signal processing, signal reconstruction, Stochastic processes, stochastic signals, Support vector machine classification, Support vector machines, SVM
@inproceedings{Vila-Forcen2008,
title = {Compressive Sensing Detection of Stochastic Signals},
author = {J E Vila-Forcen and Antonio Art\'{e}s-Rodr\'{i}guez and J Garcia-Frias},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4558656},
isbn = {978-1-4244-2246-3},
year = {2008},
date = {2008-01-01},
booktitle = {2008 42nd Annual Conference on Information Sciences and Systems},
pages = {956--960},
publisher = {IEEE},
address = {Princeton},
abstract = {Inspired by recent work in compressive sensing, we propose a framework for the detection of stochastic signals from optimized projections. In order to generate a good projection matrix, we use dimensionality reduction techniques based on the maximization of the mutual information between the projected signals and their corresponding class labels. In addition, classification techniques based on support vector machines (SVMs) are applied for the final decision process. Simulation results show that the realizations of the stochastic process are detected with higher accuracy and lower complexity than a scheme performing signal reconstruction first, followed by detection based on the reconstructed signal.},
keywords = {Additive white noise, AWGN, compressive sensing detection, dimensionality reduction techniques, Distortion measurement, Gaussian noise, matrix algebra, Mutual information, optimized projections, projection matrix, signal detection, Signal processing, signal reconstruction, Stochastic processes, stochastic signals, Support vector machine classification, Support vector machines, SVM},
pubstate = {published},
tppubtype = {inproceedings}
}
Inspired by recent work in compressive sensing, we propose a framework for the detection of stochastic signals from optimized projections. In order to generate a good projection matrix, we use dimensionality reduction techniques based on the maximization of the mutual information between the projected signals and their corresponding class labels. In addition, classification techniques based on support vector machines (SVMs) are applied for the final decision process. Simulation results show that the realizations of the stochastic process are detected with higher accuracy and lower complexity than a scheme performing signal reconstruction first, followed by detection based on the reconstructed signal.
Perez-Cruz, Fernando
Estimation of Information Theoretic Measures for Continuous Random Variables Artículo en actas
En: Advances in Neural Information Processing Systems, pp. 1257–1264, Vancouver, 2008.
@inproceedings{Perez-Cruz2008b,
title = {Estimation of Information Theoretic Measures for Continuous Random Variables},
author = {Fernando Perez-Cruz},
url = {http://papers.nips.cc/paper/3417-estimation-of-information-theoretic-measures-for-continuous-random-variables},
year = {2008},
date = {2008-01-01},
booktitle = {Advances in Neural Information Processing Systems},
pages = {1257--1264},
address = {Vancouver},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Perez-Cruz, Fernando; Murillo-Fuentes, Juan Jose; Caro, S
Nonlinear Channel Equalization With Gaussian Processes for Regression Artículo de revista
En: IEEE Transactions on Signal Processing, vol. 56, no. 10, pp. 5283–5286, 2008, ISSN: 1053-587X.
Resumen | Enlaces | BibTeX | Etiquetas: Channel estimation, digital communications receivers, equalisers, equalization, Gaussian processes, kernel adaline, least mean squares methods, maximum likelihood estimation, nonlinear channel equalization, nonlinear equalization, nonlinear minimum mean square error estimator, regression, regression analysis, short training sequences, Support vector machines
@article{Perez-Cruz2008c,
title = {Nonlinear Channel Equalization With Gaussian Processes for Regression},
author = {Fernando Perez-Cruz and Juan Jose Murillo-Fuentes and S Caro},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4563433},
issn = {1053-587X},
year = {2008},
date = {2008-01-01},
journal = {IEEE Transactions on Signal Processing},
volume = {56},
number = {10},
pages = {5283--5286},
abstract = {We propose Gaussian processes for regression (GPR) as a novel nonlinear equalizer for digital communications receivers. GPR's main advantage, compared to previous nonlinear estimation approaches, lies on their capability to optimize the kernel hyperparameters by maximum likelihood, which improves its performance significantly for short training sequences. Besides, GPR can be understood as a nonlinear minimum mean square error estimator, a standard criterion for training equalizers that trades off the inversion of the channel and the amplification of the noise. In the experiment section, we show that the GPR-based equalizer clearly outperforms support vector machine and kernel adaline approaches, exhibiting outstanding results for short training sequences.},
keywords = {Channel estimation, digital communications receivers, equalisers, equalization, Gaussian processes, kernel adaline, least mean squares methods, maximum likelihood estimation, nonlinear channel equalization, nonlinear equalization, nonlinear minimum mean square error estimator, regression, regression analysis, short training sequences, Support vector machines},
pubstate = {published},
tppubtype = {article}
}
We propose Gaussian processes for regression (GPR) as a novel nonlinear equalizer for digital communications receivers. GPR's main advantage, compared to previous nonlinear estimation approaches, lies on their capability to optimize the kernel hyperparameters by maximum likelihood, which improves its performance significantly for short training sequences. Besides, GPR can be understood as a nonlinear minimum mean square error estimator, a standard criterion for training equalizers that trades off the inversion of the channel and the amplification of the noise. In the experiment section, we show that the GPR-based equalizer clearly outperforms support vector machine and kernel adaline approaches, exhibiting outstanding results for short training sequences.
Baca-García, Enrique; Perez-Rodriguez, Mercedes M; Basurte-Villamor, Ignacio; Quintero-Gutierrez, Javier F; Sevilla-Vicente, Juncal; Martinez-Vigo, Maria; Artés-Rodríguez, Antonio; del Moral, Antonio Fernandez L; Jimenez-Arriero, Miguel A; de Rivera, Jose Gonzalez L
Patterns of Mental Health Service Utilization in a General Hospital and Outpatient Mental Health Facilities: Analysis of 365,262 Psychiatric Consultations Artículo de revista
En: European archives of psychiatry and clinical neuroscience, vol. 258, no. 2, pp. 117–123, 2008, ISSN: 0940-1334.
Resumen | Enlaces | BibTeX | Etiquetas: 80 and over, Adolescent, Adult, Age Distribution, Aged, Ambulatory Care, Ambulatory Care: statistics & numerical data, Ambulatory Care: utilization, Child, Diagnosis-Related Groups, Female, General, General: statistics & numerical data, General: utilization, Health Care Costs, Health Care Costs: statistics & numerical data, Health Services Accessibility, Health Services Accessibility: statistics & numeri, Health Services Needs and Demand, Health Services Needs and Demand: statistics & num, Hospitals, Humans, Male, Mental Disorders, Mental Disorders: classification, Mental Disorders: diagnosis, Mental Disorders: epidemiology, Mental Disorders: therapy, Mental Health Services, Mental Health Services: economics, Mental Health Services: utilization, Middle Aged, Outcome and Process Assessment (Health Care), Preschool, Psychiatry, Psychiatry: economics, Psychiatry: statistics & numerical data, Sex Distribution, Spain, Spain: epidemiology, Utilization Review, Utilization Review: statistics & numerical data
@article{Baca-Garcia2008,
title = {Patterns of Mental Health Service Utilization in a General Hospital and Outpatient Mental Health Facilities: Analysis of 365,262 Psychiatric Consultations},
author = {Enrique Baca-Garc\'{i}a and Mercedes M Perez-Rodriguez and Ignacio Basurte-Villamor and Javier F Quintero-Gutierrez and Juncal Sevilla-Vicente and Maria Martinez-Vigo and Antonio Art\'{e}s-Rodr\'{i}guez and Antonio Fernandez L del Moral and Miguel A Jimenez-Arriero and Jose Gonzalez L de Rivera},
url = {http://www.ncbi.nlm.nih.gov/pubmed/17990050},
issn = {0940-1334},
year = {2008},
date = {2008-01-01},
journal = {European archives of psychiatry and clinical neuroscience},
volume = {258},
number = {2},
pages = {117--123},
abstract = {PURPOSE: Mental health is one of the priorities of the European Commission. Studies of the use and cost of mental health facilities are needed in order to improve the planning and efficiey of mental health resources. We analyze the patterns of mental health service use in multiple clinical settings to identify factors associated with high cost. SUBJECTS AND METHODS: 22,859 patients received psychiatric care in the catchment area of a Spanish hospital (2000-2004). They had 365,262 psychiatric consultations in multiple settings. Two groups were selected that generated 80% of total costs: the medium cost group (N = 4,212; 50% of costs), and the high cost group (N = 236; 30% of costs). Statistical analyses were performed using univariate and multivariate techniques. Significant variables in univariate analyses were introduced as independent variables in a logistic regression analysis using "high cost" (>7,263$) as dependent variable. RESULTS: Costs were not evenly distributed throughout the sample. 19.4% of patients generated 80% of costs. The variables associated with high cost were: age group 1 (0-14 years) at the first evaluation, permanent disability, and ICD-10 diagnoses: Organic, including symptomatic, mental disorders; Mental and behavioural disorders due to psychoactive substance use; Schizophrenia, schizotypal and delusional disorders; Behavioural syndromes associated with physiological disturbances and physical factors; External causes of morbidity and mortality; and Factors influencing health status and contact with health services. DISCUSSION: Mental healthcare costs were not evenly distributed throughout the patient population. The highest costs are associated with early onset of the mental disorder, permanent disability, organic mental disorders, substance-related disorders, psychotic disorders, and external factors that influence the health status and contact with health services or cause morbidity and mortality. CONCLUSION: Variables related to psychiatric diagnoses and sociodemographic factors have influence on the cost of mental healthcare.},
keywords = {80 and over, Adolescent, Adult, Age Distribution, Aged, Ambulatory Care, Ambulatory Care: statistics \& numerical data, Ambulatory Care: utilization, Child, Diagnosis-Related Groups, Female, General, General: statistics \& numerical data, General: utilization, Health Care Costs, Health Care Costs: statistics \& numerical data, Health Services Accessibility, Health Services Accessibility: statistics \& numeri, Health Services Needs and Demand, Health Services Needs and Demand: statistics \& num, Hospitals, Humans, Male, Mental Disorders, Mental Disorders: classification, Mental Disorders: diagnosis, Mental Disorders: epidemiology, Mental Disorders: therapy, Mental Health Services, Mental Health Services: economics, Mental Health Services: utilization, Middle Aged, Outcome and Process Assessment (Health Care), Preschool, Psychiatry, Psychiatry: economics, Psychiatry: statistics \& numerical data, Sex Distribution, Spain, Spain: epidemiology, Utilization Review, Utilization Review: statistics \& numerical data},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: Mental health is one of the priorities of the European Commission. Studies of the use and cost of mental health facilities are needed in order to improve the planning and efficiey of mental health resources. We analyze the patterns of mental health service use in multiple clinical settings to identify factors associated with high cost. SUBJECTS AND METHODS: 22,859 patients received psychiatric care in the catchment area of a Spanish hospital (2000-2004). They had 365,262 psychiatric consultations in multiple settings. Two groups were selected that generated 80% of total costs: the medium cost group (N = 4,212; 50% of costs), and the high cost group (N = 236; 30% of costs). Statistical analyses were performed using univariate and multivariate techniques. Significant variables in univariate analyses were introduced as independent variables in a logistic regression analysis using "high cost" (>7,263$) as dependent variable. RESULTS: Costs were not evenly distributed throughout the sample. 19.4% of patients generated 80% of costs. The variables associated with high cost were: age group 1 (0-14 years) at the first evaluation, permanent disability, and ICD-10 diagnoses: Organic, including symptomatic, mental disorders; Mental and behavioural disorders due to psychoactive substance use; Schizophrenia, schizotypal and delusional disorders; Behavioural syndromes associated with physiological disturbances and physical factors; External causes of morbidity and mortality; and Factors influencing health status and contact with health services. DISCUSSION: Mental healthcare costs were not evenly distributed throughout the patient population. The highest costs are associated with early onset of the mental disorder, permanent disability, organic mental disorders, substance-related disorders, psychotic disorders, and external factors that influence the health status and contact with health services or cause morbidity and mortality. CONCLUSION: Variables related to psychiatric diagnoses and sociodemographic factors have influence on the cost of mental healthcare.
Perez-Cruz, Fernando; Murillo-Fuentes, Juan Jose
Digital Communication Receivers Using Gaussian Processes for Machine Learning Artículo de revista
En: EURASIP Journal on Advances in Signal Processing, vol. 2008, no. 1, pp. 1–13, 2008, ISSN: 1687-6172.
Resumen | Enlaces | BibTeX | Etiquetas:
@article{Perez-Cruz2008d,
title = {Digital Communication Receivers Using Gaussian Processes for Machine Learning},
author = {Fernando Perez-Cruz and Juan Jose Murillo-Fuentes},
url = {http://asp.eurasipjournals.com/content/2008/1/491503},
issn = {1687-6172},
year = {2008},
date = {2008-01-01},
journal = {EURASIP Journal on Advances in Signal Processing},
volume = {2008},
number = {1},
pages = {1--13},
publisher = {Springer},
abstract = {We propose Gaussian processes (GPs) as a novel nonlinear receiver for digital communication systems. The GPs framework can be used to solve both classification (GPC) and regression (GPR) problems. The minimum mean squared error solution is the expectation of the transmitted symbol given the information at the receiver, which is a nonlinear function of the received symbols for discrete inputs. GPR can be presented as a nonlinear MMSE estimator and thus capable of achieving optimal performance from MMSE viewpoint. Also, the design of digital communication receivers can be viewed as a detection problem, for which GPC is specially suited as it assigns posterior probabilities to each transmitted symbol. We explore the suitability of GPs as nonlinear digital communication receivers. GPs are Bayesian machine learning tools that formulates a likelihood function for its hyperparameters, which can then be set optimally. GPs outperform state-of-the-art nonlinear machine learning approaches that prespecify their hyperparameters or rely on cross validation. We illustrate the advantages of GPs as digital communication receivers for linear and nonlinear channel models for short training sequences and compare them to state-of-the-art nonlinear machine learning tools, such as support vector machines.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We propose Gaussian processes (GPs) as a novel nonlinear receiver for digital communication systems. The GPs framework can be used to solve both classification (GPC) and regression (GPR) problems. The minimum mean squared error solution is the expectation of the transmitted symbol given the information at the receiver, which is a nonlinear function of the received symbols for discrete inputs. GPR can be presented as a nonlinear MMSE estimator and thus capable of achieving optimal performance from MMSE viewpoint. Also, the design of digital communication receivers can be viewed as a detection problem, for which GPC is specially suited as it assigns posterior probabilities to each transmitted symbol. We explore the suitability of GPs as nonlinear digital communication receivers. GPs are Bayesian machine learning tools that formulates a likelihood function for its hyperparameters, which can then be set optimally. GPs outperform state-of-the-art nonlinear machine learning approaches that prespecify their hyperparameters or rely on cross validation. We illustrate the advantages of GPs as digital communication receivers for linear and nonlinear channel models for short training sequences and compare them to state-of-the-art nonlinear machine learning tools, such as support vector machines.
Leiva-Murillo, Jose M; Salcedo-Sanz, Sancho; Gallardo-Antolín, Ascensión; Artés-Rodríguez, Antonio
A Simulated Annealing Approach to Speaker Segmentation in Audio Databases Artículo de revista
En: Engineering Applications of Artificial Intelligence, vol. 21, no. 4, pp. 499–508, 2008.
Resumen | Enlaces | BibTeX | Etiquetas: Audio indexing, information theory, Simulated annealing, Speaker segmentation
@article{Leiva-Murillo2008c,
title = {A Simulated Annealing Approach to Speaker Segmentation in Audio Databases},
author = {Jose M Leiva-Murillo and Sancho Salcedo-Sanz and Ascensi\'{o}n Gallardo-Antol\'{i}n and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://www.sciencedirect.com/science/article/pii/S0952197607000954},
year = {2008},
date = {2008-01-01},
journal = {Engineering Applications of Artificial Intelligence},
volume = {21},
number = {4},
pages = {499--508},
abstract = {In this paper we present a novel approach to the problem of speaker segmentation, which is an unavoidable previous step to audio indexing. Mutual information is used for evaluating the accuracy of the segmentation, as a function to be maximized by a simulated annealing (SA) algorithm. We introduce a novel mutation operator for the SA, the Consecutive Bits Mutation operator, which improves the performance of the SA in this problem. We also use the so-called Compaction Factor, which allows the SA to operate in a reduced search space. Our algorithm has been tested in the segmentation of real audio databases, and it has been compared to several existing algorithms for speaker segmentation, obtaining very good results in the test problems considered.},
keywords = {Audio indexing, information theory, Simulated annealing, Speaker segmentation},
pubstate = {published},
tppubtype = {article}
}
In this paper we present a novel approach to the problem of speaker segmentation, which is an unavoidable previous step to audio indexing. Mutual information is used for evaluating the accuracy of the segmentation, as a function to be maximized by a simulated annealing (SA) algorithm. We introduce a novel mutation operator for the SA, the Consecutive Bits Mutation operator, which improves the performance of the SA in this problem. We also use the so-called Compaction Factor, which allows the SA to operate in a reduced search space. Our algorithm has been tested in the segmentation of real audio databases, and it has been compared to several existing algorithms for speaker segmentation, obtaining very good results in the test problems considered.
Vazquez, Manuel A; Bugallo, Monica F; Miguez, Joaquin
Sequential Monte Carlo Methods for Complexity-Constrained MAP Equalization of Dispersive MIMO Channels Artículo de revista
En: Signal Processing, vol. 88, no. 4, pp. 1017–1034, 2008.
Resumen | Enlaces | BibTeX | Etiquetas: joint channel and data estimation, Multiple Input Multiple Output (MIMO), Sequential Monte Carlo (SMC)
@article{Vazquez2008b,
title = {Sequential Monte Carlo Methods for Complexity-Constrained MAP Equalization of Dispersive MIMO Channels},
author = {Manuel A Vazquez and Monica F Bugallo and Joaquin Miguez},
url = {http://www.sciencedirect.com/science/article/pii/S0165168407003763},
year = {2008},
date = {2008-01-01},
journal = {Signal Processing},
volume = {88},
number = {4},
pages = {1017--1034},
abstract = {The ability to perform nearly optimal equalization of multiple input multiple output (MIMO) wireless channels using sequential Monte Carlo (SMC) techniques has recently been demonstrated. SMC methods allow to recursively approximate the a posteriori probabilities of the transmitted symbols, as observations are sequentially collected, using samples from adequate probability distributions. Hence, they are a class of online (adaptive) algorithms, suitable to handle the time-varying channels typical of high speed mobile communication applications. The main drawback of the SMC-based MIMO-channel equalizers so far proposed is that their computational complexity grows exponentially with the number of input data streams and the length of the channel impulse response, rendering these methods impractical. In this paper, we introduce novel SMC schemes that overcome this limitation by the adequate design of proposal probability distribution functions that can be sampled with a lesser computational burden, yet provide a close-to-optimal performance in terms of the resulting equalizer bit error rate and channel estimation error. We show that the complexity of the resulting receivers grows polynomially with the number of input data streams and the length of the channel response, and present computer simulation results that illustrate their performance in some typical scenarios.},
keywords = {joint channel and data estimation, Multiple Input Multiple Output (MIMO), Sequential Monte Carlo (SMC)},
pubstate = {published},
tppubtype = {article}
}
The ability to perform nearly optimal equalization of multiple input multiple output (MIMO) wireless channels using sequential Monte Carlo (SMC) techniques has recently been demonstrated. SMC methods allow to recursively approximate the a posteriori probabilities of the transmitted symbols, as observations are sequentially collected, using samples from adequate probability distributions. Hence, they are a class of online (adaptive) algorithms, suitable to handle the time-varying channels typical of high speed mobile communication applications. The main drawback of the SMC-based MIMO-channel equalizers so far proposed is that their computational complexity grows exponentially with the number of input data streams and the length of the channel impulse response, rendering these methods impractical. In this paper, we introduce novel SMC schemes that overcome this limitation by the adequate design of proposal probability distribution functions that can be sampled with a lesser computational burden, yet provide a close-to-optimal performance in terms of the resulting equalizer bit error rate and channel estimation error. We show that the complexity of the resulting receivers grows polynomially with the number of input data streams and the length of the channel response, and present computer simulation results that illustrate their performance in some typical scenarios.
2007
Leiva-Murillo, Jose M; Artés-Rodríguez, Antonio
Maximization of Mutual Information for Supervised Linear Feature Extraction Artículo de revista
En: IEEE Transactions on Neural Networks, vol. 18, no. 5, pp. 1433–1441, 2007, ISSN: 1045-9227.
Resumen | Enlaces | BibTeX | Etiquetas: Algorithms, Artificial Intelligence, Automated, component-by-component gradient-ascent method, Computer Simulation, Data Mining, Entropy, Feature extraction, gradient methods, gradient-based entropy, Independent component analysis, Information Storage and Retrieval, information theory, Iron, learning (artificial intelligence), Linear discriminant analysis, Linear Models, Mutual information, Optimization methods, Pattern recognition, Reproducibility of Results, Sensitivity and Specificity, supervised linear feature extraction, Vectors
@article{Leiva-Murillo2007,
title = {Maximization of Mutual Information for Supervised Linear Feature Extraction},
author = {Jose M Leiva-Murillo and Antonio Art\'{e}s-Rodr\'{i}guez},
url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=4298118},
issn = {1045-9227},
year = {2007},
date = {2007-01-01},
journal = {IEEE Transactions on Neural Networks},
volume = {18},
number = {5},
pages = {1433--1441},
publisher = {IEEE},
abstract = {In this paper, we present a novel scheme for linear feature extraction in classification. The method is based on the maximization of the mutual information (MI) between the features extracted and the classes. The sum of the MI corresponding to each of the features is taken as an heuristic that approximates the MI of the whole output vector. Then, a component-by-component gradient-ascent method is proposed for the maximization of the MI, similar to the gradient-based entropy optimization used in independent component analysis (ICA). The simulation results show that not only is the method competitive when compared to existing supervised feature extraction methods in all cases studied, but it also remarkably outperform them when the data are characterized by strongly nonlinear boundaries between classes.},
keywords = {Algorithms, Artificial Intelligence, Automated, component-by-component gradient-ascent method, Computer Simulation, Data Mining, Entropy, Feature extraction, gradient methods, gradient-based entropy, Independent component analysis, Information Storage and Retrieval, information theory, Iron, learning (artificial intelligence), Linear discriminant analysis, Linear Models, Mutual information, Optimization methods, Pattern recognition, Reproducibility of Results, Sensitivity and Specificity, supervised linear feature extraction, Vectors},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present a novel scheme for linear feature extraction in classification. The method is based on the maximization of the mutual information (MI) between the features extracted and the classes. The sum of the MI corresponding to each of the features is taken as an heuristic that approximates the MI of the whole output vector. Then, a component-by-component gradient-ascent method is proposed for the maximization of the MI, similar to the gradient-based entropy optimization used in independent component analysis (ICA). The simulation results show that not only is the method competitive when compared to existing supervised feature extraction methods in all cases studied, but it also remarkably outperform them when the data are characterized by strongly nonlinear boundaries between classes.
0000
Pradier, Melanie F.; Hyland, Stephanie L.; Stark, Stefan G.; Lehmann, Kjong; Vogt, Julia E.; Perez-Cruz, Fernando; Rätsch, Gunnar
A Bayesian Nonparametric Approach to Discover Clinico-Genetic Associations across Cancer Types Artículo de revista En preparación
En: En preparación.
Enlaces | BibTeX | Etiquetas: Bayesian non parametrics
@article{FPerez18c,
title = {A Bayesian Nonparametric Approach to Discover Clinico-Genetic Associations across Cancer Types},
author = {Melanie F. Pradier and Stephanie L. Hyland and Stefan G. Stark and Kjong Lehmann and Julia E. Vogt and Fernando Perez-Cruz and Gunnar R\"{a}tsch},
doi = {https://doi.org/10.1101/623215},
keywords = {Bayesian non parametrics},
pubstate = {forthcoming},
tppubtype = {article}
}
Mariño, Inés P.; Pérez-Vieites, Sara; Míguez, Joaquín
Parameter Estimation and State Forecasting in Meteorological Models Conferencia
BOOK OF ABSTRACTS, 0000, (The 6th International Conference on Complex Networks & Their Applications. Nov. 29 - Dec. 01, 2017, Lyon (France)).
BibTeX | Etiquetas:
@conference{nokey,
title = {Parameter Estimation and State Forecasting in Meteorological Models},
author = {In\'{e}s P. Mari\~{n}o and Sara P\'{e}rez-Vieites and Joaqu\'{i}n M\'{i}guez},
booktitle = {BOOK OF ABSTRACTS},
pages = {178},
note = {The 6th International Conference on Complex Networks \&
Their Applications. Nov. 29 - Dec. 01, 2017, Lyon (France)},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}