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Applied Neural Networks for Signal Processing

Applied Neural Networks for Signal Processing
Author: Fa-Long Luo
Publisher: Cambridge University Press
Total Pages: 388
Release: 1998
Genre: Computers
ISBN: 9780521644006

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A comprehensive introduction to the use of neural networks in signal processing.


Handbook of Neural Network Signal Processing

Handbook of Neural Network Signal Processing
Author: Yu Hen Hu
Publisher: CRC Press
Total Pages: 408
Release: 2018-10-03
Genre: Technology & Engineering
ISBN: 1420038613

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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.


Application of Signal Processing Tools and Artificial Neural Network in Diagnosis of Power System Faults

Application of Signal Processing Tools and Artificial Neural Network in Diagnosis of Power System Faults
Author: Nabamita Banerjee Roy
Publisher: CRC Press
Total Pages: 144
Release: 2021-07-21
Genre: Technology & Engineering
ISBN: 1000414906

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Explores methods of fault identification through programming and simulation in MATLAB Examines signal processing tools and their applications with examples Provides knowledge of artificial neural networks and their applications with illustrations Uses PNN and BPNN to identify the different types of faults and obtain their corresponding locations Discusses the programming of signal processing using Wavelet Transform and S-Transform


Neural Networks for Optimization and Signal Processing

Neural Networks for Optimization and Signal Processing
Author: Andrzej Cichocki
Publisher: John Wiley & Sons
Total Pages: 578
Release: 1993-06-07
Genre: Computers
ISBN:

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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.


Applying Neural Networks

Applying Neural Networks
Author: Kevin Swingler
Publisher: Morgan Kaufmann
Total Pages: 348
Release: 1996
Genre: Computers
ISBN: 9780126791709

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This book is designed to enable the reader to design and run a neural network-based project. It presents everything the reader will need to know to ensure the success of such a project. The book contains a free disk with C and C++ programs, which implement many of the techniques discussed in the book.


Process Neural Networks

Process Neural Networks
Author: Xingui He
Publisher: Springer Science & Business Media
Total Pages: 240
Release: 2010-07-05
Genre: Computers
ISBN: 3540737626

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For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.


Applied Neural Networks for Signal Processing

Applied Neural Networks for Signal Processing
Author: F. L. Luo
Publisher:
Total Pages: 367
Release: 1998
Genre:
ISBN:

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Fundamental models of neural networks for signal processing; Neural networks for filtering; Neural networks for spectral estimation; neural networks for signal detection; Neural networks for signal reconstruction; Neural networks for adaptive extraction of principal and minor components; Neural networks for array signal processing; Neural networks for system identification; Neural networks for signal compression.


Speech, Audio, Image and Biomedical Signal Processing using Neural Networks

Speech, Audio, Image and Biomedical Signal Processing using Neural Networks
Author: Bhanu Prasad
Publisher: Springer Science & Business Media
Total Pages: 419
Release: 2008-01-03
Genre: Computers
ISBN: 3540753974

Download Speech, Audio, Image and Biomedical Signal Processing using Neural Networks Book in PDF, ePub and Kindle

Humans are remarkable in processing speech, audio, image and some biomedical signals. Artificial neural networks are proved to be successful in performing several cognitive, industrial and scientific tasks. This peer reviewed book presents some recent advances and surveys on the applications of artificial neural networks in the areas of speech, audio, image and biomedical signal processing. It chapters are prepared by some reputed researchers and practitioners around the globe.


Fuzzy Systems and Soft Computing in Nuclear Engineering

Fuzzy Systems and Soft Computing in Nuclear Engineering
Author: Da Ruan
Publisher: Springer Science & Business Media
Total Pages: 506
Release: 2000-01-14
Genre: Business & Economics
ISBN: 9783790812510

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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.