Info
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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Forecasting and Risk Management Techniques for Electricity Markets
| Forecasting and Risk Management Techniques for Electricity Markets |
| Autore | Yamada Yuji |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (212 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
artificial market simulation
balancing power market bidding agent bidding strategy blockchain cashflow management of electricity businesses cooperative mechanism cyclic cubic spline day-ahead market demonstration experiment digital grid distributed energy resources distributed energy resources (DER) electric vehicle electric vehicles electricity derivatives and forwards electricity load electricity markets electricity price electricity price forecasting empirical simulations functional autoregressive model functional final prediction error (FFPE) functional principle component analysis hardware control home energy management systems intra-day market liquidity market maker microgrid minimum variance hedge multi agent system n/a naive method non-parametric regression optimal hedging using nonparametric techniques P2P electricity market P2P energy trading peer to peer energy market peer-to-peer energy trading price fluctuation renewable energy retailers and power producers solar power and thermal energy spline basis functions vector autoregressive model weather derivatives wind energy |
| ISBN | 3-0365-5184-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619464203321 |
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Yamada Yuji
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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