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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 online resource (296 p.) |
| Soggetto topico |
Mathematics & science
Research & information: general |
| Soggetto non controllato |
aging in human population
Alzheimer's disease approximate entropy autonomic nervous function autonomic nervous system baroreflex baroreflex sensitivity (BRS) biomarker blood pressure brain brain dynamics brain functional networks brain signals cardiovascular system central autonomic network cognitive task complexity complexity analysis conditional transfer entropy correlation dimension cross-entropy data compression detrended fluctuation analysis digital volume pulse (DVP) dynamic functional connectivity ECG ectopic beat entropy event-related de/synchronization factor analysis fetal heart rate fNIRS fractal dimension fragmentation fuzzy entropy heart rate heart rate variability heart rate variability (HRV) hypobaric hypoxia information dynamics information flow interconnectivity K-means clustering algorithm labor largest Lyapunov exponent linear prediction mental arithmetics motor imagery multifractality multiscale multiscale complexity multivariate time series analysis network physiology nonlinear analysis partial information decomposition penalized regression techniques percussion entropy index (PEI) photo-plethysmo-graphy (PPG) posture preterm recurrence quantification analysis refined composite multiscale entropy rehabilitation medicine relative consistency Sampen sample entropy self-organized criticality self-similarity sEMG single-channel analysis State-space models static functional connectivity support vector machines classification time series analysis vasovagal syncope vector autoregressive model vector quantization Zipf's law |
| 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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