Assessment of Variability in Irregularly Sampled Time Series: Applications to Mental Healthcare

Mathematics (p. 1-18) - 1/2021

https://doi.org/10.3390/math9010071 Ver en origen

• ISSN 2227-7390

• UC3M

Assessment of e-Social Activity in Psychiatric Patients

IEEE Journal of Biomedical and Health Informatics (p. 2247-2256) - 5/2019

https://doi.org/10.1109/jbhi.2019.2918687 Ver en origen

• EISSN 2168-2208
• ISSN 2168-2194

• UC3M

Canonical correlation analysis of high-dimensional data with very small sample support

SIGNAL PROCESSING (p. 449-458) - 11/2016

https://doi.org/10.1016/j.sigpro.2016.05.020 Ver en origen

• EISSN 1872-7557
• ISSN 0165-1684

• UC3M

Change-point detection in hierarchical circadian models

PATTERN RECOGNITION (p. 107820) - 5/2021

https://doi.org/10.1016/j.patcog.2021.107820 Ver en origen

• ISSN 0031-3203

• UC3M

Combining Continuous Smartphone Native Sensors Data Capture and Unsupervised Data Mining Techniques for Behavioral Changes Detection: A Case Series of the Evidence-Based Behavior (eB2) Study

JMIR mHealth and uHealth - 12/2018

https://doi.org/10.2196/mhealth.9472 Ver en origen

• ISSN 2291-5222

• UC3M

Detection of multivariate cyclostationarity

IEEE TRANSACTIONS ON SIGNAL PROCESSING (p. 5395-5408) - 10/2015

https://doi.org/10.1109/tsp.2015.2450201 Ver en origen

• EISSN 1941-0476
• ISSN 1053-587X

• UC3M

Graph-signal reconstruction and blind deconvolution for structured inputs

SIGNAL PROCESSING - 1/11/2021

https://doi.org/10.1016/j.sigpro.2021.108180 Ver en origen

• EISSN 1872-7557
• ISSN 01651684

• iMarina
• UC3M

Joint Detection of Almost-Cyclostationary Signals and Estimation of Their Cycle Period

IEEE SIGNAL PROCESSING LETTERS - 11/2018

10.1109/lsp.2018.2871961 Ver en origen

• EISSN 1558-2361
• ISSN 1070-9908

• UC3M

LMPIT-Inspired Tests for Detecting a Cyclostationary Signal in Noise With Spatio-Temporal Structure

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (p. 6321-6334) - 9/2018

10.1109/twc.2018.2859314 Ver en origen

• EISSN 1558-2248
• ISSN 1536-1276

• UC3M

Multi-channel factor analysis with common and unique factors

IEEE TRANSACTIONS ON SIGNAL PROCESSING (p. 113-126) - 1/2020

https://doi.org/10.1109/tsp.2019.2955829 Ver en origen

• EISSN 1941-0476
• ISSN 1053-587X

• UC3M

Coherence: In Signal Processing and Machine Learning

2023

https://doi.org/10.1007/978-3-031-13331-2 Ver en origen

• ISBN 978-3-031-13331-2

• UC3M

A general test for the linear structure of covariance matrices of Gaussian populations

2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2020) (p. 5365-5369) - 2020

Editor: IEEE.THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

http://doi.org/10.1109/icassp40776.2020.9053718 Ver en origen

• ISBN 978-1-5090-6631-5

• UC3M

An alternating optimization algorithm for two-channel factor analysis with common and uncommon factors

52nd Asilomar Conference on Signals, Systems and Computers (ASILOMAR 2018) (p. 1743-1747) - 2018

Editor: IEEE Computer Society.

https://doi.org/10.1109/acssc.2018.8645457 Ver en origen

• ISBN 978-1-5386-9218-9

• UC3M

An asymptotic LMPI test for cyclostationarity detection with application to cognitive radio

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (p. 5669-5673) - 2015

Editor: IEEE Computer Society.

10.1109/icassp.2015.7179057 Ver en origen

• ISBN 978-1-4673-6997-8

• UC3M

Bootstrap-based detection of the number of signals correlated across multiple data sets

50th Asilomar Annual Conference on Signals, Systems and Computers (ASILOMAR 2015) (p. 610-614) - 2016

https://doi.org/10.1109/acssc.2016.7869115 Ver en origen

• UC3M

Continual learning for infinite hierarchical change-point detection

2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2020) (p. 3582-3586) - 2020

Editor: IEEE.THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/icassp40776.2020.9053853 Ver en origen

• ISBN 978-1-5090-6631-5

• UC3M

Demixing and blind deconvolution of graph-diffused sparse signals

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (p. 4189-4193) - 1/1/2018

Editor: IEEE.THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/icassp.2018.8462154 Ver en origen

• ISBN 978-1-5386-4658-8
• ISSN 15206149

• iMarina
• iMarina
• UC3M

Detecting the dimension of the subspace correlated across multiple data sets in the sample poor regime

IEEE Statistical Signal Processing Workshop (SSP 2016) (p. 1-5) - 2016

Editor: IEEE.THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/ssp.2016.7551708 Ver en origen

• ISBN 978-1-4673-7802-4

• UC3M

Detection of almost-cyclostationarity: An approach based on a multiple hypothesis test

51st Asilomar Annual Conference on Signals, Systems and Computers (ASILOMAR 2017) (p. 1635-1639) - 2017

Editor: IEEE Computer Society.

10.1109/acssc.2017.8335636 Ver en origen

• ISBN 2576-2303

• UC3M

Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio

41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016) (p. 4249-4253) - 2016

Editor: IEEE.THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/icassp.2016.7472478 Ver en origen

• ISBN 978-1-4799-9988-0

• UC3M

Determining the number of signals correlated across multiple data sets for small sample support

24th European Signal Processing Conference (EUSIPC 2016) (p. 1528-1532) - 2015

Editor: IEEE.THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, INC

https://doi.org/10.1109/eusipco.2016.7760504 Ver en origen

• ISBN 978-0-9928-6265-7

• UC3M

Objective Assessment of Psychiatric Patients via Machine Learning

Fecha de defensa: 16-03-2022

• UC3M