Complex Valued Nonlinear Adaptive Filters
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Complex Valued Nonlinear Adaptive Filters
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Author : Danilo P. Mandic
language : en
Publisher: John Wiley & Sons
Release Date : 2009-04-20
Complex Valued Nonlinear Adaptive Filters written by Danilo P. Mandic and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-20 with Science categories.
This book was written in response to the growing demand for a text that provides a unified treatment of linear and nonlinear complex valued adaptive filters, and methods for the processing of general complex signals (circular and noncircular). It brings together adaptive filtering algorithms for feedforward (transversal) and feedback architectures and the recent developments in the statistics of complex variable, under the powerful frameworks of CR (Wirtinger) calculus and augmented complex statistics. This offers a number of theoretical performance gains, which is illustrated on both stochastic gradient algorithms, such as the augmented complex least mean square (ACLMS), and those based on Kalman filters. This work is supported by a number of simulations using synthetic and real world data, including the noncircular and intermittent radar and wind signals.
Adaptive Signal Processing
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Author : Tülay Adali
language : en
Publisher: John Wiley & Sons
Release Date : 2010-06-25
Adaptive Signal Processing written by Tülay Adali and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-25 with Science categories.
Leading experts present the latest research results in adaptive signal processing Recent developments in signal processing have made it clear that significant performance gains can be achieved beyond those achievable using standard adaptive filtering approaches. Adaptive Signal Processing presents the next generation of algorithms that will produce these desired results, with an emphasis on important applications and theoretical advancements. This highly unique resource brings together leading authorities in the field writing on the key topics of significance, each at the cutting edge of its own area of specialty. It begins by addressing the problem of optimization in the complex domain, fully developing a framework that enables taking full advantage of the power of complex-valued processing. Then, the challenges of multichannel processing of complex-valued signals are explored. This comprehensive volume goes on to cover Turbo processing, tracking in the subspace domain, nonlinear sequential state estimation, and speech-bandwidth extension. Examines the seven most important topics in adaptive filtering that will define the next-generation adaptive filtering solutions Introduces the powerful adaptive signal processing methods developed within the last ten years to account for the characteristics of real-life data: non-Gaussianity, non-circularity, non-stationarity, and non-linearity Features self-contained chapters, numerous examples to clarify concepts, and end-of-chapter problems to reinforce understanding of the material Contains contributions from acknowledged leaders in the field Adaptive Signal Processing is an invaluable tool for graduate students, researchers, and practitioners working in the areas of signal processing, communications, controls, radar, sonar, and biomedical engineering.
Adaptive Filters
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Author : Ali H. Sayed
language : en
Publisher: Wiley-IEEE Press
Release Date : 2008-04-14
Adaptive Filters written by Ali H. Sayed and has been published by Wiley-IEEE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-14 with Science categories.
"Adaptive Filters allows readers to gain a gradual and solid introduction to the subject, its applications to a variety of topical problems, existing limitations, and extensions of current theories. - This book will interest students, experts, practitioners and instructors."--BOOK JACKET.
Mendel 2015
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Author : Radek Matoušek
language : en
Publisher: Springer
Release Date : 2015-06-14
Mendel 2015 written by Radek Matoušek and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-14 with Technology & Engineering categories.
This book is a collection of selected accepted papers of Mendel conference that has been held in Brno, Czech Republic in June 2015. The book contents three chapters which represent recent advances in soft computing including intelligent image processing and bio-inspired robotics.: Chapter 1: Evolutionary Computing, and Swarm intelligence, Chapter 2: Neural Networks, Self-organization, and Machine Learning, and Chapter3: Intelligent Image Processing, and Bio-inspired Robotics. The Mendel conference was established in 1995, and it carries the name of the scientist and Augustinian priest Gregor J. Mendel who discovered the famous Laws of Heredity. In 2015 we are commemorating 150 years since Mendel's lectures, which he presented in Brno on February and March 1865. The main aim of the conference was to create a periodical possibility for students, academics and researchers to exchange their ideas and novel research methods.
Neural Information Processing
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Author : Sabri Arik
language : en
Publisher: Springer
Release Date : 2015-11-21
Neural Information Processing written by Sabri Arik and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-21 with Computers categories.
The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.
Machine Learning
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Author : Sergios Theodoridis
language : en
Publisher: Academic Press
Release Date : 2020-02-19
Machine Learning written by Sergios Theodoridis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-19 with Technology & Engineering categories.
Machine Learning: A Bayesian and Optimization Perspective, 2nd edition, gives a unified perspective on machine learning by covering both pillars of supervised learning, namely regression and classification. The book starts with the basics, including mean square, least squares and maximum likelihood methods, ridge regression, Bayesian decision theory classification, logistic regression, and decision trees. It then progresses to more recent techniques, covering sparse modelling methods, learning in reproducing kernel Hilbert spaces and support vector machines, Bayesian inference with a focus on the EM algorithm and its approximate inference variational versions, Monte Carlo methods, probabilistic graphical models focusing on Bayesian networks, hidden Markov models and particle filtering. Dimensionality reduction and latent variables modelling are also considered in depth. This palette of techniques concludes with an extended chapter on neural networks and deep learning architectures. The book also covers the fundamentals of statistical parameter estimation, Wiener and Kalman filtering, convexity and convex optimization, including a chapter on stochastic approximation and the gradient descent family of algorithms, presenting related online learning techniques as well as concepts and algorithmic versions for distributed optimization. Focusing on the physical reasoning behind the mathematics, without sacrificing rigor, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. Most of the chapters include typical case studies and computer exercises, both in MATLAB and Python. The chapters are written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as courses on sparse modeling, deep learning, and probabilistic graphical models. New to this edition: - Complete re-write of the chapter on Neural Networks and Deep Learning to reflect the latest advances since the 1st edition. The chapter, starting from the basic perceptron and feed-forward neural networks concepts, now presents an in depth treatment of deep networks, including recent optimization algorithms, batch normalization, regularization techniques such as the dropout method, convolutional neural networks, recurrent neural networks, attention mechanisms, adversarial examples and training, capsule networks and generative architectures, such as restricted Boltzman machines (RBMs), variational autoencoders and generative adversarial networks (GANs). - Expanded treatment of Bayesian learning to include nonparametric Bayesian methods, with a focus on the Chinese restaurant and the Indian buffet processes. - Presents the physical reasoning, mathematical modeling and algorithmic implementation of each method - Updates on the latest trends, including sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling - Provides case studies on a variety of topics, including protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, and more
Neural Information Processing
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Author : Derong Liu
language : en
Publisher: Springer
Release Date : 2017-11-07
Neural Information Processing written by Derong Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-07 with Computers categories.
The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.
Neural Information Processing
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Author : Chu Kiong Loo
language : en
Publisher: Springer
Release Date : 2014-10-20
Neural Information Processing written by Chu Kiong Loo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-20 with Computers categories.
The three volume set LNCS 8834, LNCS 8835, and LNCS 8836 constitutes the proceedings of the 21st International Conference on Neural Information Processing, ICONIP 2014, held in Kuching, Malaysia, in November 2014. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The selected papers cover major topics of theoretical research, empirical study, and applications of neural information processing research. The 3 volumes represent topical sections containing articles on cognitive science, neural networks and learning systems, theory and design, applications, kernel and statistical methods, evolutionary computation and hybrid intelligent systems, signal and image processing, and special sessions intelligent systems for supporting decision, making processes, theories and applications, cognitive robotics, and learning systems for social network and web mining.
Self Organizing Maps
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Author : Josphat Igadwa Mwasiagi
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-01-21
Self Organizing Maps written by Josphat Igadwa Mwasiagi and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-21 with Computers categories.
Kohonen Self Organizing Maps (SOM) has found application in practical all fields, especially those which tend to handle high dimensional data. SOM can be used for the clustering of genes in the medical field, the study of multi-media and web based contents and in the transportation industry, just to name a few. Apart from the aforementioned areas this book also covers the study of complex data found in meteorological and remotely sensed images acquired using satellite sensing. Data management and envelopment analysis has also been covered. The application of SOM in mechanical and manufacturing engineering forms another important area of this book. The final section of this book, addresses the design and application of novel variants of SOM algorithms.
Orthogonal Waveforms And Filter Banks For Future Communication Systems
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Author : Markku Renfors
language : en
Publisher: Academic Press
Release Date : 2017-07-14
Orthogonal Waveforms And Filter Banks For Future Communication Systems written by Markku Renfors and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-14 with Computers categories.
Orthogonal Waveforms and Filter Banks for Future Communication Systems provides an up-to-date account of orthogonal filter bank-based multicarrier (FBMC) systems and their applications in modern and future communications, highlighting the crucial role that advanced multicarrier waveforms play. It is an up-to-date overview of the theory, algorithms, design and applications of FBMC systems at both the link- and system levels that demonstrates the various gains offered by FBMC over existing transmission schemes via both simulation and test bed experiments. Readers will learn the requirements and challenges of advanced waveform design for future communication systems, existing FBMC approaches, application areas, and their implementation. In addition, the state-of-the-art in PHY- and MAC-layer solutions based on FBMC techniques, including theoretical, algorithmic and implementation aspects are explored. - Presents a unique and up-to-date source for signal processing/communications researchers and practitioners - Presents a homogeneous, comprehensive presentation of the subject - Covers offset-QAM based FBMC (FBMC/OQAM) and its variants, including its history, signal processing interest and potential for maximum spectral efficiency, among other features