LEADER 05916nam 2200625Ia 450 001 9910139054403321 005 20230803023655.0 010 $a1-118-62216-2 010 $a1-118-62214-6 010 $a1-118-62215-4 035 $a(CKB)2560000000102102 035 $a(EBL)1207774 035 $a(OCoLC)850079007 035 $a(MiAaPQ)EBC1207774 035 $a(DLC) 2013007202 035 $a(Au-PeEL)EBL1207774 035 $a(CaPaEBR)ebr10716700 035 $a(CaONFJC)MIL497265 035 $a(EXLCZ)992560000000102102 100 $a20130215d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aAdaptive processing of brain signals$b[electronic resource] /$fSaeid Sanei 210 $aChichester, West Sussex $cJohn Wiley & Sons Inc.$dc2013 215 $a1 online resource (1039 p.) 300 $aDescription based upon print version of record. 311 $a0-470-68613-8 320 $aIncludes bibliographical references and index. 327 $aCover; Title Page; Copyright; Preface; Chapter 1 Brain Signals, Their Generation, Acquisition and Properties; 1.1 Introduction; 1.2 Historical Review of the Brain; 1.3 Neural Activities; 1.4 Action Potentials; 1.5 EEG Generation; 1.6 Brain Rhythms; 1.7 EEG Recording and Measurement; 1.8 Abnormal EEG Patterns; 1.9 Aging; 1.10 Mental Disorders; 1.11 Memory and Content Retrieval; 1.12 MEG Signals and Their Generation; 1.13 Conclusions; References; Chapter 2 Fundamentals of EEG Signal Processing; 2.1 Introduction; 2.2 Nonlinearity of the Medium; 2.3 Nonstationarity; 2.4 Signal Segmentation 327 $a2.5 Other Properties of Brain Signals2.6 Conclusions; References; Chapter 3 EEG Signal Modelling; 3.1 Physiological Modelling of EEG Generation; 3.2 Mathematical Models; 3.3 Generating EEG Signals Based on Modelling the Neuronal Activities; 3.4 Electronic Models; 3.5 Dynamic Modelling of the Neuron Action Potential Threshold; 3.6 Conclusions; References; Chapter 4 Signal Transforms and Joint Time-Frequency Analysis; 4.1 Introduction; 4.2 Parametric Spectrum Estimation and Z-Transform; 4.3 Time-Frequency Domain Transforms; 4.4 Ambiguity Function and the Wigner-Ville Distribution 327 $a4.5 Hermite Transform4.6 Conclusions; References; Chapter 5 Chaos and Dynamical Analysis; 5.1 Entropy; 5.2 Kolmogorov Entropy; 5.3 Lyapunov Exponents; 5.4 Plotting the Attractor Dimensions from Time Series; 5.5 Estimation of Lyapunov Exponents from Time Series; 5.6 Approximate Entropy; 5.7 Using Prediction Order; 5.8 Conclusions; References; Chapter 6 Classification and Clustering of Brain Signals; 6.1 Introduction; 6.2 Linear Discriminant Analysis; 6.3 Support Vector Machines; 6.4 k-Means Algorithm; 6.5 Common Spatial Patterns; 6.6 Conclusions; References 327 $aChapter 7 Blind and Semi-Blind Source Separation7.1 Introduction; 7.2 Singular Spectrum Analysis; 7.3 Independent Component Analysis; 7.4 Instantaneous BSS; 7.5 Convolutive BSS; 7.6 Sparse Component Analysis; 7.7 Nonlinear BSS; 7.8 Constrained BSS; 7.9 Application of Constrained BSS; Example; 7.10 Nonstationary BSS; 7.11 Tensor Factorization for Underdetermined Source Separation; 7.12 Tensor Factorization for Separation of Convolutive Mixtures in the Time Domain; 7.13 Separation of Correlated Sources via Tensor Factorization; 7.14 Conclusions; References 327 $aChapter 8 Connectivity of Brain Regions8.1 Introduction; 8.2 Connectivity Through Coherency; 8.3 Phase-Slope Index; 8.4 Multivariate Directionality Estimation; 8.5 Modelling the Connectivity by Structural Equation Modelling; 8.6 EEG Hyper-Scanning and Inter-Subject Connectivity; 8.7 State-Space Model for Estimation of Cortical Interactions; 8.8 Application of Adaptive Filters; 8.9 Tensor Factorization Approach; 8.10 Conclusions; References; Chapter 9 Detection and Tracking of Event-Related Potentials; 9.1 ERP Generation and Types; 9.2 Detection, Separation, and Classification of P300 Signals 327 $a9.3 Brain Activity Assessment Using ERP 330 $a"Brain signal processing spans a broad range of knowledge across engineering, science and medicine, and this book brings together the disparate theory and application to create a comprehensive resource on this growing topic. It will provide advanced tools for the detection, monitoring, separation, localizing and understanding of brain functional, anatomical, and physiological abnormalities. The focus will be on advanced and adaptive signal processing techniques for the processing of electroencephalography and magneto-encephalography signals, and their correlation to the corresponding functional magnetic resonance imaging (fMRI). Multimodal processing of brain signals, the new focus for brain signal research, will also be explored. The book covers the broad remit of neuro-imaging, ensuring comprehensive coverage of all issues related to brain signal processing. Topics such as mental fatigue, brain connectivity and new recording techniques will also be covered.This book will be a progression/follow on from Dr Sanei's first book with Wiley, EEG Signal Processing"--$cProvided by publisher. 330 $a"Covers the fundamentals of brain signal processing, before developing the subject at advanced level"--$cProvided by publisher. 606 $aBrain$xPhysiology 606 $aNeural networks (Neurobiology) 606 $aSignal processing$xDigital techniques 615 0$aBrain$xPhysiology. 615 0$aNeural networks (Neurobiology) 615 0$aSignal processing$xDigital techniques. 676 $a573.8/5 686 $aSCI067000$2bisacsh 700 $aSanei$b Saeid$0629068 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139054403321 996 $aAdaptive processing of brain signals$92000934 997 $aUNINA