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Automated Eeg Based Diagnosis Of Neurological Disorders

Author: Hojjat Adeli
Publisher: CRC Press
ISBN: 9781439815328
Size: 29.13 MB
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Based on the authors’ groundbreaking research, Automated EEG-Based Diagnosis of Neurological Disorders: Inventing the Future of Neurology presents a research ideology, a novel multi-paradigm methodology, and advanced computational models for the automated EEG-based diagnosis of neurological disorders. It is based on the ingenious integration of three different computing technologies and problem-solving paradigms: neural networks, wavelets, and chaos theory. The book also includes three introductory chapters that familiarize readers with these three distinct paradigms. After extensive research and the discovery of relevant mathematical markers, the authors present a methodology for epilepsy diagnosis and seizure detection that offers an exceptional accuracy rate of 96 percent. They examine technology that has the potential to impact and transform neurology practice in a significant way. They also include some preliminary results towards EEG-based diagnosis of Alzheimer’s disease. The methodology presented in the book is especially versatile and can be adapted and applied for the diagnosis of other brain disorders. The senior author is currently extending the new technology to diagnosis of ADHD and autism. A second contribution made by the book is its presentation and advancement of Spiking Neural Networks as the seminal foundation of a more realistic and plausible third generation neural network.

Future Generation Information Technology

Author: Jung-Hyun Lee
Publisher: Springer
ISBN: 3642175694
Size: 24.72 MB
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As information technology (IT) becomes specialized and fragmented, it is easy to lose sight that many topics have common threads and because of this, advances in one s- discipline may transmit to another. The presentation of results between different s- disciplines encourages this interchange for the advancement of IT as a whole. This volume comprises the selection of papers presented at the Second International Mega-Conference on Future Generation Information Technology (FGIT 2010), composed of the following 11 international conferences: Advanced Software Engineering and Its Applications (ASEA 2010), Bio-Science and Bio- Technology (BSBT 2010), Control and Automation (CA 2010), Disaster Recovery and Business Continuity (DRBC 2010), Database Theory and Application (DTA 2010), Future Generation Communication and Networking (FGCN 2010), Grid and Distributed Computing (GDC 2010), Multimedia, Computer Graphics and Broadcasting (MulGraB 2010), Security Technology (SecTech 2010), Signal Processing, Image Processing and Pattern Recognition (SIP 2010), as well as u- and e-Service, Science and Technology (UNESST 2010). In total, 1,630 papers were submitted to FGIT 2010 from 30 countries. The submitted papers went through a rigorous reviewing process and 395 papers were accepted. Of these 395 papers, 60 were assigned to this volume. In addition, this volume contains 7 invited papers and abstracts. Of the remaining accepted papers, 269 were distributed among 8 volumes of proceedings published by Springer in the CCIS series. 66 papers were withdrawn due to technical reasons.

Neural Information Processing

Author: Akira Hirose
Publisher: Springer
ISBN: 331946681X
Size: 35.66 MB
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The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.

Advanced Signal Processing On Brain Event Related Potentials

Author: Fengyu Cong
Publisher: World Scientific
ISBN: 9814623105
Size: 37.26 MB
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This book is devoted to the application of advanced signal processing on event-related potentials (ERPs) in the context of electroencephalography (EEG) for the cognitive neuroscience. ERPs are usually produced through averaging single-trials of preprocessed EEG, and then, the interpretation of underlying brain activities is based on the ordinarily averaged EEG. We find that randomly fluctuating activities and artifacts can still present in the averaged EEG data, and that constant brain activities over single trials can overlap with each other in time, frequency and spatial domains. Therefore, before interpretation, it will be beneficial to further separate the averaged EEG into individual brain activities. The book proposes systematic approaches pre-process wavelet transform (WT), independent component analysis (ICA), and nonnegative tensor factorization (NTF) to filter averaged EEG in time, frequency and space domains to sequentially and simultaneously obtain the pure ERP of interest. Software of the proposed approaches will be open-accessed. Contents:IntroductionWavelet Filter Design Based on Frequency Responses for Filtering ERP Data With Duration of One EpochIndividual-Level ICA to Extract the ERP Components from the Averaged EEG DataMulti-Domain Feature of the ERP Extracted by NTF: New Approach for Group-Level Analysis of ERPsAnalysis of Ongoing EEG by NTF During Real-World Music ExperiencesAppendix: Introduction to Basic Knowledge of Mismatch Negativity Readership: Undergraduate, graduate, researchers and professionals in the field of neurology/neuroscience, medical imaging, psychology, biomedical engineering and computer science. Key Features:Advanced signal processing approaches can be applied on averaged EEG to extract ERPs' componentsFiltering ERPs in time, frequency and space domains sequentially and simultaneouslyDemo of ERP data and MATLAB codes are open-access for the advanced signal processing approaches on ERPsKeywords:Event-Related Potentials (ERPs);Digital Filter;Wavelet Filter;Independent Component Analysis;Tensor Decomposition;Nonnegative Tensor Factorization;Time-Frequency Representation

Advanced Models Of Neural Networks

Author: Gerasimos Rigatos
Publisher: Springer
ISBN: 3662437643
Size: 72.83 MB
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This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory. It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory.