LEADER 04438nam 22005655 450 001 9910482987003321 005 20200702111440.0 010 $a3-319-95098-3 024 7 $a10.1007/978-3-319-95098-3 035 $a(CKB)4100000005323423 035 $a(DE-He213)978-3-319-95098-3 035 $a(MiAaPQ)EBC5472011 035 $a(PPN)229501575 035 $a(EXLCZ)994100000005323423 100 $a20180721d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNeural Advances in Processing Nonlinear Dynamic Signals /$fedited by Anna Esposito, Marcos Faundez-Zanuy, Francesco Carlo Morabito, Eros Pasero 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XII, 318 p. 91 illus., 61 illus. in color.) 225 1 $aSmart Innovation, Systems and Technologies,$x2190-3018 ;$v102 311 $a3-319-95097-5 327 $aProcessing Nonlinearities -- Temporal Artifacts from Edge Accumulation in Social Interaction -- Data Mining by Evolving Agents for Clusters Discovery and Metric Learning -- Error Resilient Neural Networks on Low-Dimensional Manifolds -- On 4-Dimensional Hypercomplex Algebras in Adaptive Signal Processing -- Growing Curvilinear Component Analysis (GCCA) for Stator Fault Detection in Induction Machines -- Convolutional Neural Networks for the Identification of Filaments from Fast Visual Imaging Cameras in Tokamak Reactors -- Appraisal of Enhanced Surrogate Models for Substrate Integrate Waveguide Devices Characterization -- An Improved PSO for Flexible Parameters Identification of Lithium Cells Equivalent Circuit Models -- New Challenges in Pension Industry: Proposals of Personal Pension Products -- A Method Based on OWA Operator for Scientific Research Evaluation -- A Cluster Analysis Approach for Rule Base Reduction. 330 $aThis book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals from arrays of sensors, and perturbations in the automatic control of industrial production processes. It also discusses the drastic changes in financial, economic, and work processes that are currently being experienced by the computational and engineering sciences community. Addresses key aspects, such as the integration of neural algorithms and procedures for the recognition, the analysis and detection of dynamic complex structures and the implementation of systems for discovering patterns in data, the book highlights the commonalities between computational intelligence (CI) and information and communications technologies (ICT) to promote transversal skills and sophisticated processing techniques. This book is a valuable resource for a. The academic research community b. The ICT market c. PhD students and early stage researchers d. Companies, research institutes e. Representatives from industry and standardization bodies. 410 0$aSmart Innovation, Systems and Technologies,$x2190-3018 ;$v102 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aComputational complexity 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComplexity$3https://scigraph.springernature.com/ontologies/product-market-codes/T11022 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aComputational complexity. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aComplexity. 676 $a006.3 702 $aEsposito$b Anna$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aFaundez-Zanuy$b Marcos$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMorabito$b Francesco Carlo$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPasero$b Eros$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910482987003321 996 $aNeural advances in processing nonlinear dynamic signals$91535861 997 $aUNINA