Search results: Found 7

Listing 1 - 7 of 7
Sort by
Information Decomposition of Target Effects from Multi-Source Interactions

Authors: --- --- ---
ISBN: 9783038970156 9783038970163 Year: Pages: 336 DOI: 10.3390/books978-3-03897-016-3 Language: englisch
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mathematics --- Physics (General)
Added to DOAB on : 2018-09-04 13:22:10
License:

Loading...
Export citation

Choose an application

Abstract

Using Shannon information theory to analyse the contributions from two source variables to a target, for example, we can measure the information held by one source about the target, the information held by the other source about the target, and the information held by those sources together about the target. Intuitively, however, there is strong desire to measure further notions of how this directed information interaction may be decomposed, e.g., how much information the two source variables hold redundantly about the target, how much each source variable holds uniquely, and how much information can only be discerned by synergistically examining the two sources together.The absence of measures for such decompositions into redundant, unique and synergistic information is arguably the most fundamental missing piece in classical information theory. Triggered by the formulation of the Partial Information Decomposition framework by Williams and Beer in 2010, the past few years have witnessed a concentration of work by the community in proposing, contrasting, and investigating new measures to capture these notions of information decomposition.This Special Issue seeks to bring together these efforts, to capture a snapshot of the current research, as well as to provide impetus for and focused scrutiny on newer work, present progress to the wider community and attract further research. Our contributions present: several new approaches for measures of such decompotions; commentary on properties, interpretations and limitations of such approaches; and applications to empirical data (in particular to neural data).

Information-based methods for neuroimaging: analyzing structure, function and dynamics

Authors: --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889195022 Year: Pages: 191 DOI: 10.3389/978-2-88919-502-2 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2015-12-03 13:02:24
License:

Loading...
Export citation

Choose an application

Abstract

The aim of this Research Topic is to discuss the state of the art on the use of Information-based methods in the analysis of neuroimaging data. Information-based methods, typically built as extensions of the Shannon Entropy, are at the basis of model-free approaches which, being based on probability distributions rather than on specific expectations, can account for all possible non-linearities present in the data in a model-independent fashion.Mutual Information-like methods can also be applied on interacting dynamical variables described by time-series, thus addressing the uncertainty reduction (or information) in one variable by conditioning on another set of variables.In the last years, different Information-based methods have been shown to be flexible and powerful tools to analyze neuroimaging data, with a wide range of different methodologies, including formulations-based on bivariate vs multivariate representations, frequency vs time domains, etc. Apart from methodological issues, the information bit as a common unit represents a convenient way to open the road for comparison and integration between different measurements of neuroimaging data in three complementary contexts: Structural Connectivity, Dynamical (Functional and Effective) Connectivity, and Modelling of brain activity. Applications are ubiquitous, starting from resting state in healthy subjects to modulations of consciousness and other aspects of pathophysiology.Mutual Information-based methods have provided new insights about common-principles in brain organization, showing the existence of an active default network when the brain is at rest. It is not clear, however, how this default network is generated, the different modules are intra-interacting, or disappearing in the presence of stimulation. Some of these open-questions at the functional level might find their mechanisms on their structural correlates. A key question is the link between structure and function and the use of structural priors for the understanding of the functional connectivity measures. As effective connectivity is concerned, recently a common framework has been proposed for Transfer Entropy and Granger Causality, a well-established methodology originally based on autoregressive models. This framework can open the way to new theories and applications.This Research Topic brings together contributions from researchers from different backgrounds which are either developing new approaches, or applying existing methodologies to new data, and we hope it will set the basis for discussing the development and validation of new Information-based methodologies for the understanding of brain structure, function, and dynamics.

Transfer Entropy

Author:
ISBN: 9783038429197 9783038429203 Year: Pages: VIII, 326 Language: Englisch
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2018-08-24 17:15:19
License:

Loading...
Export citation

Choose an application

Abstract

Statistical relationships among the variables of a complex system reveal a lot about its physical behavior. Therefore, identification of the relevant variables and characterization of their interactions are crucial for a better understanding of a complex system. Linear methods, such as correlation, are widely used to identify these relationships. However, information-theoretic quantities, such as mutual information and transfer entropy, have been proven to be superior in the case of nonlinear dependencies. Mutual information quantifies the amount of information obtained about one random variable through the other random variable, and it is symmetric. As an asymmetrical measure, transfer entropy quantifies the amount of directed (time-asymmetric) transfer of information between random processes and, thus, it is related to concepts, such as the Granger causality. This Special Issue includes 16 papers elucidating the state of the art of data-based transfer entropy estimation techniques and applications, in areas such as finance, biomedicine, fluid dynamics and cellular automata. Analytical derivations in special cases, improvements on the estimation methods and comparisons between certain techniques are some of the other contributions of this Special Issue. The diversity of approaches and applications makes this book unique as a single source of invaluable contributions from experts in the field.

Information Theory in Neuroscience

Authors: ---
ISBN: 9783038976646 Year: Pages: 280 DOI: 10.3390/books978-3-03897-665-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mathematics --- Science (General)
Added to DOAB on : 2019-03-21 15:50:41
License:

Loading...
Export citation

Choose an application

Abstract

As the ultimate information processing device, the brain naturally lends itself to being studied with information theory. The application of information theory to neuroscience has spurred the development of principled theories of brain function, and has led to advances in the study of consciousness, as well as to the development of analytical techniques to crack the neural code—that is, to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling the precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative testing of hypotheses about how the brain encodes and transmits the information used for specific functions across areas. This Special Issue presents twelve original contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience.

Entropy Applications in Environmental and Water Engineering

Authors: --- ---
ISBN: 9783038972228 Year: Pages: 512 DOI: 10.3390/books978-3-03897-223-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Environmental Engineering --- General and Civil Engineering --- Technology (General)
Added to DOAB on : 2019-03-21 15:50:41
License:

Loading...
Export citation

Choose an application

Abstract

Entropy theory has wide applications to a range of problems in the fields of environmental and water engineering, including river hydraulic geometry, fluvial hydraulics, water monitoring network design, river flow forecasting, floods and droughts, river network analysis, infiltration, soil moisture, sediment transport, surface water and groundwater quality modeling, ecosystems modeling, water distribution networks, environmental and water resources management, and parameter estimation. Such applications have used several different entropy formulations, such as Shannon, Tsallis, Reacutenyi Burg, Kolmogorov, Kapur, configurational, and relative entropies, which can be derived in time, space, or frequency domains. More recently, entropy-based concepts have been coupled with other theories, including copula and wavelets, to study various issues associated with environmental and water resources systems. Recent studies indicate the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering, including establishing and explaining physical connections between theory and reality. The objective of this Special Issue is to provide a platform for compiling important recent and current research on the applications of entropy theory in environmental and water engineering. The contributions to this Special Issue have addressed many aspects associated with entropy theory applications and have shown the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering.

Keywords

complexity --- streamflow --- water level --- composite multiscale sample entropy --- trend --- Poyang Lake basin --- four-parameter exponential gamma distribution --- principle of maximum entropy --- precipitation frequency analysis --- methods of moments --- maximum likelihood estimation --- flood frequency analysis --- generalized gamma (GG) distribution --- principle of maximum entropy (POME) --- entropy theory --- principle of maximum entropy (POME) --- GB2 distribution --- flood frequency analysis --- non-point source pollution --- ANN --- entropy weighting method --- data-scarce --- multi-events --- spatio-temporal variability --- soil water content --- entropy --- arid region --- joint entropy --- NDVI --- temperature --- precipitation --- groundwater depth --- Hei River basin --- turbulent flow --- canopy flow --- randomness --- coherent structures --- Shannon entropy --- Kolmogorov complexity --- entropy --- information transfer --- optimization --- radar --- rainfall network --- water resource carrying capacity --- forewarning model --- entropy of information --- fuzzy analytic hierarchy process --- projection pursuit --- accelerating genetic algorithm --- entropy production --- conditional entropy production --- stochastic processes --- scaling --- climacogram --- turbulence --- water resources vulnerability --- connection entropy --- changing environment --- set pair analysis --- Anhui Province --- cross-entropy minimization --- land suitability evaluation --- spatial optimization --- monthly streamflow forecasting --- Burg entropy --- configurational entropy --- entropy spectral analysis time series analysis --- entropy --- water monitoring --- network design --- hydrometric network --- information theory --- entropy applications --- hydrological risk analysis --- maximum entropy-copula method --- uncertainty --- Loess Plateau --- entropy --- water engineering --- Tsallis entropy --- principle of maximum entropy --- Lagrangian function --- probability distribution function --- flux concentration relation --- uncertainty --- information --- informational entropy --- variation of information --- continuous probability distribution functions --- confidence intervals --- precipitation --- variability --- marginal entropy --- crop yield --- Hexi corridor --- flow duration curve --- Shannon entropy --- entropy parameter --- modeling --- spatial and dynamics characteristic --- hydrology --- tropical rainfall --- statistical scaling --- Tsallis entropy --- multiplicative cascades --- Beta-Lognormal model --- rainfall forecast --- cross entropy --- ant colony fuzzy clustering --- combined forecast --- information entropy --- mutual information --- kernel density estimation --- ENSO --- nonlinear relation --- scaling laws --- power laws --- water distribution networks --- robustness --- flow entropy --- entropy theory --- frequency analysis --- hydrometeorological extremes --- Bayesian technique --- rainfall --- entropy ensemble filter --- ensemble model simulation criterion --- EEF method --- bootstrap aggregating --- bagging --- bootstrap neural networks --- El Niño --- ENSO --- neural network forecast --- sea surface temperature --- tropical Pacific --- entropy --- cross elasticity --- mean annual runoff --- water resources --- resilience --- quaternary catchment --- complement --- substitute --- entropy theory --- complex systems --- hydraulics --- hydrology --- water engineering --- environmental engineering

Optimization Methods Applied to Power Systems: Volume 1

Authors: ---
ISBN: 9783039211302 / 9783039211319 Year: Pages: 382 DOI: 10.3390/books978-3-03921-131-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
License:

Loading...
Export citation

Choose an application

Abstract

This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.

Keywords

Cable joint --- internal defect --- thermal probability density --- power system optimization --- optimal power flow --- developed grew wolf optimizer --- energy internet --- prosumer --- energy management --- consensus --- demand response --- day-ahead load forecasting --- modular predictor --- feature selection --- micro-phasor measurement unit --- mutual information theory --- stochastic state estimation --- two-point estimation method --- JAYA algorithm --- multi-population method (MP) --- chaos optimization algorithm (COA) --- economic load dispatch problem (ELD) --- optimization methods --- constrained parameter estimation --- extended Kalman filter --- power systems --- C&I particle swarm optimization --- ringdown detection --- optimal reactive power dispatch --- loss minimization --- voltage deviation --- hybrid method --- tabu search --- particle swarm optimization --- artificial lighting --- simulation --- calibration --- radiance --- GenOpt --- street light points --- DC optimal power flow --- power transfer distribution factors --- generalized generation distribution factors --- unit commitment --- adaptive consensus algorithm --- distributed heat-electricity energy management --- eight searching sub-regions --- islanded microgrid --- dragonfly algorithm --- metaheuristic --- optimal power flow --- particle swarm optimization --- CCHP system --- energy storage --- off-design performance --- dynamic solving framework --- battery energy storage system --- micro grid --- MILP --- PCS efficiency --- piecewise linear techniques --- renewable energy sources --- optimal operation --- UC --- demand bidding --- demand response --- genetic algorithm --- load curtailment --- optimization --- hybrid renewable energy system --- pumped-hydro energy storage --- off-grid --- optimization --- HOMER software --- rural electrification --- sub-Saharan Africa --- Cameroon --- building energy management system --- HVAC system --- energy storage system --- energy flow model --- dependability --- sustainability --- data center --- power architectures --- optimization --- AC/DC hybrid active distribution --- hierarchical scheduling --- multi-stakeholders --- discrete wind driven optimization --- multiobjective optimization --- optimal power flow --- metaheuristic --- wind energy --- photovoltaic --- smart grid --- transformer-fault diagnosis --- principal component analysis --- particle swarm optimization --- support vector machine --- wind power --- integration assessment --- interactive load --- considerable decomposition --- controllable response --- SOCP relaxations --- optimal power flow --- current margins --- affine arithmetic --- interval variables --- optimizing-scenarios method --- power flow --- wind power --- active distribution system --- virtual power plant --- stochastic optimization --- decentralized and collaborative optimization --- genetic algorithm --- multi-objective particle swarm optimization algorithm --- artificial bee colony --- IEEE Std. 80-2000 --- Schwarz’s equation --- fuzzy algorithm --- radial basis function --- neural network --- ETAP --- distributed generations (DGs) --- distribution network reconfiguration --- runner-root algorithm (RRA) --- inter-turn shorted-circuit fault (ISCF) --- strong track filter (STF) --- linear discriminant analysis (LDA) --- switched reluctance machine (SRM) --- charging/discharging --- electric vehicle --- energy management --- genetic algorithm --- intelligent scatter search --- electric vehicles --- heterogeneous networks --- demand uncertainty --- power optimization --- Stackelberg game --- power system unit commitment --- hybrid membrane computing --- cross-entropy --- the genetic algorithm based P system --- the biomimetic membrane computing --- transient stability --- two-stage feature selection --- particle encoding method --- fitness function --- power factor compensation --- non-sinusoidal circuits --- geometric algebra --- evolutionary algorithms --- electric power contracts --- electric energy costs --- cost minimization --- evolutionary computation --- bio-inspired algorithms --- congestion management --- low-voltage networks --- multi-objective particle swarm optimization --- affinity propagation clustering --- optimal congestion threshold --- optimization --- magnetic field mitigation --- overhead --- underground --- passive shielding --- active shielding --- MV/LV substation --- n/a

Optimization Methods Applied to Power Systems: Volume 2

Authors: ---
ISBN: 9783039211562 / 9783039211579 Year: Pages: 306 DOI: 10.3390/books978-3-03921-157-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
License:

Loading...
Export citation

Choose an application

Abstract

This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.

Keywords

Cable joint --- internal defect --- thermal probability density --- power system optimization --- optimal power flow --- developed grew wolf optimizer --- energy internet --- prosumer --- energy management --- consensus --- demand response --- day-ahead load forecasting --- modular predictor --- feature selection --- micro-phasor measurement unit --- mutual information theory --- stochastic state estimation --- two-point estimation method --- JAYA algorithm --- multi-population method (MP) --- chaos optimization algorithm (COA) --- economic load dispatch problem (ELD) --- optimization methods --- constrained parameter estimation --- extended Kalman filter --- power systems --- C&I particle swarm optimization --- ringdown detection --- optimal reactive power dispatch --- loss minimization --- voltage deviation --- hybrid method --- tabu search --- particle swarm optimization --- artificial lighting --- simulation --- calibration --- radiance --- GenOpt --- street light points --- DC optimal power flow --- power transfer distribution factors --- generalized generation distribution factors --- unit commitment --- adaptive consensus algorithm --- distributed heat-electricity energy management --- eight searching sub-regions --- islanded microgrid --- dragonfly algorithm --- metaheuristic --- optimal power flow --- particle swarm optimization --- CCHP system --- energy storage --- off-design performance --- dynamic solving framework --- battery energy storage system --- micro grid --- MILP --- PCS efficiency --- piecewise linear techniques --- renewable energy sources --- optimal operation --- UC --- demand bidding --- demand response --- genetic algorithm --- load curtailment --- optimization --- hybrid renewable energy system --- pumped-hydro energy storage --- off-grid --- optimization --- HOMER software --- rural electrification --- sub-Saharan Africa --- Cameroon --- building energy management system --- HVAC system --- energy storage system --- energy flow model --- dependability --- sustainability --- data center --- power architectures --- optimization --- AC/DC hybrid active distribution --- hierarchical scheduling --- multi-stakeholders --- discrete wind driven optimization --- multiobjective optimization --- optimal power flow --- metaheuristic --- wind energy --- photovoltaic --- smart grid --- transformer-fault diagnosis --- principal component analysis --- particle swarm optimization --- support vector machine --- wind power --- integration assessment --- interactive load --- considerable decomposition --- controllable response --- SOCP relaxations --- optimal power flow --- current margins --- affine arithmetic --- interval variables --- optimizing-scenarios method --- power flow --- wind power --- active distribution system --- virtual power plant --- stochastic optimization --- decentralized and collaborative optimization --- genetic algorithm --- multi-objective particle swarm optimization algorithm --- artificial bee colony --- IEEE Std. 80-2000 --- Schwarz’s equation --- fuzzy algorithm --- radial basis function --- neural network --- ETAP --- distributed generations (DGs) --- distribution network reconfiguration --- runner-root algorithm (RRA) --- inter-turn shorted-circuit fault (ISCF) --- strong track filter (STF) --- linear discriminant analysis (LDA) --- switched reluctance machine (SRM) --- charging/discharging --- electric vehicle --- energy management --- genetic algorithm --- intelligent scatter search --- electric vehicles --- heterogeneous networks --- demand uncertainty --- power optimization --- Stackelberg game --- power system unit commitment --- hybrid membrane computing --- cross-entropy --- the genetic algorithm based P system --- the biomimetic membrane computing --- transient stability --- two-stage feature selection --- particle encoding method --- fitness function --- power factor compensation --- non-sinusoidal circuits --- geometric algebra --- evolutionary algorithms --- electric power contracts --- electric energy costs --- cost minimization --- evolutionary computation --- bio-inspired algorithms --- congestion management --- low-voltage networks --- multi-objective particle swarm optimization --- affinity propagation clustering --- optimal congestion threshold --- optimization --- magnetic field mitigation --- overhead --- underground --- passive shielding --- active shielding --- MV/LV substation --- n/a

Listing 1 - 7 of 7
Sort by
Narrow your search