Applied Neural Networks for Signal Processing PDF Download
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Author: Fa-Long Luo
Publisher: Cambridge University Press
ISBN: 9780521644006
Category : Computers
Languages : en
Pages : 388
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Book Description
A comprehensive introduction to the use of neural networks in signal processing.
Author: Fa-Long Luo
Publisher: Cambridge University Press
ISBN: 9780521644006
Category : Computers
Languages : en
Pages : 388
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Book Description
A comprehensive introduction to the use of neural networks in signal processing.
Author: Jose Principe
Publisher:
ISBN: 9780780342576
Category : Neural networks (Computer science)
Languages : en
Pages : 667
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Book Description
Author: Bart Kosko
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 424
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Book Description
Edited by a leading expert in neural networks, this collection of essays explores neural network applications in signal and image processing, function and estimation, robotics and control, associative memories, and electrical and optical neural networks. This reference will be of interest to scientists, engineers, and others working in the neural network field.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Yu Hen Hu
Publisher: CRC Press
ISBN: 1420038613
Category : Technology & Engineering
Languages : en
Pages : 408
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Book Description
The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing. The Handbook of Neural Network Signal Processing brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view. The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech, communication, geophysical, sonar, radar, medical, and many other signals. The subject of neural networks and their application to signal processing is constantly improving. You need a handy reference that will inform you of current applications in this new area. The Handbook of Neural Network Signal Processing provides this much needed service for all engineers and scientists in the field.
Author: Andrzej Cichocki
Publisher: John Wiley & Sons
ISBN:
Category : Computers
Languages : en
Pages : 578
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Book Description
A topical introduction on the ability of artificial neural networks to not only solve on-line a wide range of optimization problems but also to create new techniques and architectures. Provides in-depth coverage of mathematical modeling along with illustrative computer simulation results.
Author: Anthony Zaknich
Publisher: World Scientific
ISBN: 9814486469
Category : Computers
Languages : en
Pages : 510
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Book Description
This book provides a thorough theoretical and practical introduction to the application of neural networks to pattern recognition and intelligent signal processing. It has been tested on students, unfamiliar with neural networks, who were able to pick up enough details to successfully complete their masters or final year undergraduate projects. The text also presents a comprehensive treatment of a class of neural networks called common bandwidth spherical basis function NNs, including the probabilistic NN, the modified probabilistic NN and the general regression NN.
Author: Jong Chul Ye
Publisher: Springer Nature
ISBN: 9811660468
Category : Mathematics
Languages : en
Pages : 338
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Book Description
The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually the case in many existing deep learning books, here, deep learning is explained as an ultimate form of signal processing techniques that can be imagined. To support this claim, an overview of classical kernel machine learning approaches is presented, and their advantages and limitations are explained. Following a detailed explanation of the basic building blocks of deep neural networks from a biological and algorithmic point of view, the latest tools such as attention, normalization, Transformer, BERT, GPT-3, and others are described. Here, too, the focus is on the fact that in these heuristic approaches, there is an important, beautiful geometric structure behind the intuition that enables a systematic understanding. A unified geometric analysis to understand the working mechanism of deep learning from high-dimensional geometry is offered. Then, different forms of generative models like GAN, VAE, normalizing flows, optimal transport, and so on are described from a unified geometric perspective, showing that they actually come from statistical distance-minimization problems. Because this book contains up-to-date information from both a practical and theoretical point of view, it can be used as an advanced deep learning textbook in universities or as a reference source for researchers interested in acquiring the latest deep learning algorithms and their underlying principles. In addition, the book has been prepared for a codeshare course for both engineering and mathematics students, thus much of the content is interdisciplinary and will appeal to students from both disciplines.
Author: Yu Hen Hu
Publisher: CRC Press
ISBN: 1351836307
Category : Technology & Engineering
Languages : en
Pages : 386
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Book Description
The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing. The Handbook of Neural Network Signal Processing brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view. The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech, communication, geophysical, sonar, radar, medical, and many other signals. The subject of neural networks and their application to signal processing is constantly improving. You need a handy reference that will inform you of current applications in this new area. The Handbook of Neural Network Signal Processing provides this much needed service for all engineers and scientists in the field.
Author: Da Ruan
Publisher: Springer Science & Business Media
ISBN: 9783790812510
Category : Business & Economics
Languages : en
Pages : 506
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Book Description
This book is an organized edited collection of twenty-one contributed chapters covering nuclear engineering applications of fuzzy systems, neural networks, genetic algorithms and other soft computing techniques. All chapters are either updated review or original contributions by leading researchers written exclusively for this volume. The volume highlights the advantages of applying fuzzy systems and soft computing in nuclear engineering, which can be viewed as complementary to traditional methods. As a result, fuzzy sets and soft computing provide a powerful tool for solving intricate problems pertaining in nuclear engineering. Each chapter of the book is self-contained and also indicates the future research direction on this topic of applications of fuzzy systems and soft computing in nuclear engineering.
