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Image analysis is a fundamental task for extracting information from images acquired across a range of different devices. Since reliable quantitative results are requested, image analysis requires highly sophisticated numerical and analytical methods—particularly for applications in medicine, security, and remote sensing, where the results of the processing may consist of vitally important data. The contributions to this book provide a good overview of the most important demands and solutions concerning this research area. In particular, the reader will find image analysis applied for feature extraction, encryption and decryption of data, color segmentation, and in the support new technologies. In all the contributions, entropy plays a pivotal role.
image retrieval  multifeature fusion  entropy  relevance feedback  chaotic system  image encryption  permutationdiffusion  SHA256 hash value  dynamic index  entropy  keyframes  Shannon’s entropy  sign languages  video summarization  video skimming  image encryption  multipleimage encryption  twodimensional chaotic economic map  security analysis  image encryption  chaotic cryptography  cryptanalysis  chosenplaintext attack  image information entropy  blind image quality assessment (BIQA)  information entropy, natural scene statistics (NSS)  Weibull statistics  discrete cosine transform (DCT)  ultrasound  hepatic steatosis  Shannon entropy  fatty liver  metabolic syndrome  multiexposure image fusion  texture information entropy  adaptive selection  patch structure decomposition  image encryption  timedelay  random insertion  information entropy  chaotic map  uncertainty assessment  deep neural network  random forest  Shannon entropy  positron emission tomography  reconstruction  field of experts  additive manufacturing  3D prints  3D scanning  image entropy  depth maps  surface quality assessment  machine vision  image analysis  Arimoto entropy  freeform deformations  normalized divergence measure  gradient distributions  nonextensive entropy  nonrigid registration  pavement  macrotexture  3D digital imaging  entropy  decay trend  discrete entropy  infrared images  low contrast  multiscale tophat transform  image encryption  DNA encoding  chaotic cryptography  cryptanalysis  image privacy  computer aided diagnostics  colonoscopy  Rényi entropies  structural entropy  spatial filling factor  binary image  Cantor set  Hénon map  Minkowski island  primeindexed primes  Ramanujan primes  Kapur’s entropy  color image segmentation  whale optimization algorithm  differential evolution  hybrid algorithm  Otsu method  image encryption  dynamic filtering  DNA computing  3D Latin cube  permutation  diffusion  fuzzy entropy  electromagnetic field optimization  chaotic strategy  color image segmentation  multilevel thresholding  contrast enhancement  sigmoid  Tsallis statistics  qexponential  qsigmoid  qGaussian  ultrasound images  person reidentification  image analysis  hash layer  quantization loss  Hamming distance  crossentropy loss  image entropy  Shannon entropy  generalized entropies  image processing  image segmentation  medical imaging  remote sensing  security
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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, entropybased 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.
complexity  streamflow  water level  composite multiscale sample entropy  trend  Poyang Lake basin  fourparameter 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  nonpoint source pollution  ANN  entropy weighting method  datascarce  multievents  spatiotemporal 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  crossentropy 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 entropycopula 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  BetaLognormal 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
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Entropies and entropylike quantities play an increasing role in modern nonlinear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropybased coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.
experiment of design  empirical mode decomposition  signal analysis  similarity indices  synchronization analysis  auditory attention  entropy measure  linear discriminant analysis (LDA)  support vector machine (SVM)  auditory attention classifier  electroencephalography (EEG)  vague entropy  distance induced vague entropy  distance  complex fuzzy set  complex vague soft set  entropy, entropy visualization  entropy balance equation  Shannontype relations  multivariate analysis  machine learning evaluation  data transformation  sample entropy  treadmill walking  center of pressure displacement  dualtasking  analog circuit  fault diagnosis  cross wavelet transform  Tsallis entropy  parametric tdistributed stochastic neighbor embedding  support vector machine  information transfer  Chinese stock sectors  effective transfer entropy  market crash  system coupling  crossvisibility graphs  image entropy  geodesic distance  DempsterShafer evidence theory  uncertainty of basic probability assignment  belief entropy  plausibility transformation  weighted Hartley entropy  Shannon entropy  learning  information  novelty detection  nonprobabilistic entropy  learning systems  permutation entropy  embedded dimension  short time records  signal classification  relevance analysis  global optimization  metaheuristic  firefly algorithm  crossentropy method  coevolution  symbolic analysis  ordinal patterns  Permutation entropy  conditional entropy of ordinal patterns  KolmogorovSinai entropy  algorithmic complexity  information entropy  particle size distribution  selfsimilar measure  simulation  data analysis  entropy  entropy measures  automatic learning
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This Special Issue with 35 published articles shows the significance of the topic “Signal Processing and Analysis of Electrical Circuit”. This topic has been gaining increasing attention in recent times. The presented articles can be categorized into four different areas: signal processing and analysis methods of electrical circuits; electrical measurement technology; applications of signal processing of electrical equipment; fault diagnosis of electrical circuits. It is a fact that the development of electrical systems, signal processing methods, and circuits has been accelerating. Electronics applications related to electrical circuits and signal processing methods have gained noticeable attention in recent times. The methods of signal processing and electrical circuits are widely used by engineers and scientists all over the world. The constituent papers represent a significant contribution to electronics and present applications that can be used in industry. Further improvements to the presented approaches are required for realizing their full potential.
VMD  signal analysis  ICEEMD  IMF  random noise  attenuation  commutator motor  fault diagnosis  method  technique  signal processing  acoustic  Inner and outer product  tensor  FPGA  hardware  direct digital synthesizer (DDS)  frequency tuning word (FTW)  stability  accuracy  demodulation  phaselocked loop  Chebyshev filter  measurement noise suppression  class AB operation  CMOS  current mirror  current buffer  quasi floating gate  low power  CMOS  dynamic comparator  offset calibration  high speed  low noise  low power  ADC  allpass filter  CMOS  time delay  broadband  truetimedelay  electrochemical impedance spectroscopy  FRA  multichannel acquisition  impedance spectrometry  microcontroller  intelligent vehicles  LiDAR odometry  range sensing  simultaneous localization and mapping (SLAM)  tilt sensor  sensor data fusion  complementary filters  overlapadd processing  spectral analysis  variational mode decomposition (VMD)  duffing chaotic oscillator (DCO)  permutation entropy (PE)  feature extraction  frequency characteristic  underwater acoustic signal  shipradiated noise  PM/PWM  capacitancetotime conversion  differential capacitive sensor  brickwall filter  fuzzy logic  induction motor  Shannon entropy  shortcircuit fault  APF  CNFET  polefrequency  chirality  phase angle  tuning  DC–DC converter  switched capacitor  power management integrated circuit  CMOS technology  frequency standard comparator  dual Mixing Time difference  phase difference  correlation function  chebyshev polynomial  compressed sensing  estimated sparsity  least squares solution  stochastic gradient  reconstruction probability  direct position determination  array signal processing  Doppler shifts  matrix eigenperturbation theory  system errors  Cramér–Rao bound  differential power analysis (DPA), SIMON  fault injection  double rate  power randomization  intention of movement classification  EMGSignals  Support Vector Machines  asynchronous  delay cell  passive resistor  SAR ADC  loop delay circuit  ResistancetoPeriod converter  robust readout circuits  ratiometric technique  Fresnel lens  wingbeat  insects  optoelectronics  bees  wasps  fruit flies  etraps  analogtodigital converter  successive approximation register  direct sampling  timeinterleaved  channelselectionembedded bootstrap  segmented prequantization and bypass  LVDS  highspeed serial interface  transmitter  receiver  lowpower  image fusion  multisensor fusion  night vision  hierarchical heterogeneous multiDAG workflow  multigroup scan  ultrasonic phased array  heterogeneous earliest finish time  resolver  discrete wavelet transform  singular value decomposition  automatic calibration  noise reduction  ripple voltage measurement  DAC  comparator  peakripple estimation  binary search  lowcost  secret image sharing  digital image  noutofn scheme  color palette  colluder attack  image restoration  impulse noise  ADMM  HOCTVL1  spatially adapted regularization parameter  rod electrode  electrostatic induction  method of images  induced charge  induced current  3DIC design  NILT  TSV noise coupling  RDL  chain matrix  interconnect line  n/a
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