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Assessing Complexity in Physiological Systems through Biomedical Signals Analysis
| Assessing Complexity in Physiological Systems through Biomedical Signals Analysis |
| Autore | Castiglioni Paolo |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (296 p.) |
| Soggetto topico |
Research & information: general
Mathematics & science |
| Soggetto non controllato |
autonomic nervous function
heart rate variability (HRV) baroreflex sensitivity (BRS) photo-plethysmo-graphy (PPG) digital volume pulse (DVP) percussion entropy index (PEI) heart rate variability posture entropy complexity cognitive task sample entropy brain functional networks dynamic functional connectivity static functional connectivity K-means clustering algorithm fragmentation aging in human population factor analysis support vector machines classification Sampen cross-entropy autonomic nervous system heart rate blood pressure hypobaric hypoxia rehabilitation medicine labor fetal heart rate data compression complexity analysis nonlinear analysis preterm Alzheimer’s disease brain signals single-channel analysis biomarker refined composite multiscale entropy central autonomic network interconnectivity ECG ectopic beat baroreflex self-organized criticality vasovagal syncope Zipf’s law multifractality multiscale complexity detrended fluctuation analysis self-similarity sEMG approximate entropy fuzzy entropy fractal dimension recurrence quantification analysis correlation dimension largest Lyapunov exponent time series analysis relative consistency event-related de/synchronization motor imagery vector quantization information dynamics partial information decomposition conditional transfer entropy network physiology multivariate time series analysis State–space models vector autoregressive model penalized regression techniques linear prediction fNIRS brain dynamics mental arithmetics multiscale cardiovascular system brain information flow |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557601803321 |
Castiglioni Paolo
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Information Theory and Machine Learning
| Information Theory and Machine Learning |
| Autore | Zheng Lizhong |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (254 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
supervised classification
independent and non-identically distributed features analytical error probability empirical risk generalization error K-means clustering model compression population risk rate distortion theory vector quantization overfitting information criteria entropy model-based clustering merging mixture components component overlap interpretability time series prediction finite state machines hidden Markov models recurrent neural networks reservoir computers long short-term memory deep neural network information theory local information geometry feature extraction spiking neural network meta-learning information theoretic learning minimum error entropy artificial general intelligence closed-loop transcription linear discriminative representation rate reduction minimax game fairness HGR maximal correlation independence criterion separation criterion pattern dictionary atypicality Lempel–Ziv algorithm lossless compression anomaly detection information-theoretic bounds distribution and federated learning |
| ISBN | 3-0365-5308-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619463403321 |
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Zheng Lizhong
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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