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Neural Networks for Optimization and Signal Processing by Andrzej Cichocki Wiley
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eBay-Artikelnr.:127476520130
Artikelmerkmale
- Artikelzustand
- Book Title
- Neural Networks for Optimization and Signal Processing
- ISBN-13
- 9780471930105
- ISBN
- 9780471930105
Über dieses Produkt
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0471930105
ISBN-13
9780471930105
eBay Product ID (ePID)
1037025
Product Key Features
Number of Pages
544 Pages
Publication Name
Neural Networks for Optimization and Signal Processing
Language
English
Subject
Game Theory, Neural Networks
Publication Year
1993
Type
Textbook
Subject Area
Mathematics, Computers
Format
Hardcover
Dimensions
Item Height
1.5 in
Item Weight
33.1 Oz
Item Length
9.2 in
Item Width
6.2 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
92-046543
Illustrated
Yes
Table Of Content
Mathematical Preliminaries of Neurocomputing. Architectures and Electronic Implementation of Neural Network Models. Unconstrained Optimization and Learning Algorithms. Neural Networks for Linear, Quadratic Programming and Linear Complementarity Problems. A Neural Network Approach to the On-Line Solution of a System of Linear Algebraic Equations and Related Problems. Neural Networks for Matrix Algebra Problems. Neural Networks for Continuous, Nonlinear, Constrained Optimization Problems. Neural Networks for Estimation, Identification and Prediction. Neural Networks for Discrete and Combinatorial Optimization Problems. Appendices. Subject Index.
Synopsis
Neural Networks for Optimization and Signal Processing A. Cichocki Warsaw University of Technology Poland R. Unbehauen Universität Erlangen-Nürnberg Germany Artificial neural networks can be employed to solve a wide spectrum of problems in optimization, parallel computing, matrix algebra and signal processing. Taking a computational approach, this book explains how ANNs provide solutions in real time, and allow the visualization and development of new techniques and architectures. Features include: A guide to the fundamental mathematics of neurocomputing. A review of neural network models and an analysis of their associated algorithms. State-of-the-art procedures to solve optimization problems. Computer simulation programs MATLAB, TUTSIM and SPICE illustrate the validity and performance of the algorithms and architectures described. The authors encourage the reader to be creative in visualizing new approaches and detail how other specialized computer programs can evaluate performance. Each chapter concludes with a short bibliography. Illustrative worked examples, questions and problems assist self study. The authors self-contained approach will appeal to a wide range of readers, including professional engineers working in computing, optimization, operational research, systems identification and control theory. Undergraduate and postgraduate students in computer science, electrical and electronic engineering will also find this text invaluable. In particular, the text will be ideal to supplement courses in circuit analysis and design, adaptive systems, control systems, signal processing and parallel computing. B.G. Teubner Stuttgart, Artificial neural networks can be employed to solve a wide spectrum of problems in optimization, parallel computing, matrix algebra and signal processing. Taking a computational approach, this book explains how ANNs provide solutions in real time, and allow the visualization and development of new techniques and architectures. Features include a guide to the fundamental mathematics of neurocomputing, a review of neural network models and an analysis of their associated algorithms, and state-of-the-art procedures to solve optimization problems. Computer simulation programs MATLAB, TUTSIM and SPICE illustrate the validity and performance of the algorithms and architectures described. The authors encourage the reader to be creative in visualizing new approaches and detail how other specialized computer programs can evaluate performance. Each chapter concludes with a short bibliography. Illustrative worked examples, questions and problems assist self study. The authors' self-contained approach will appeal to a wide range of readers, including professional engineers working in computing, optimization, operational research, systems identification and control theory. Undergraduate and postgraduate students in computer science, electrical and electronic engineering will also find this text invaluable. In particular, the text will be ideal to supplement courses in circuit analysis and design, adaptive systems, control systems, signal processing and parallel computing., 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.
LC Classification Number
QA76.87.C52 1993
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A Fresh Purpose
97,1% positive Bewertungen•176 Artikel verkauft
Angemeldet als privater VerkäuferDaher finden verbraucherschützende Vorschriften, die sich aus dem EU-Verbraucherrecht ergeben, keine Anwendung. Der eBay-Käuferschutz gilt dennoch für die meisten Käufe. Mehr erfahrenMehr erfahren
Verkäuferbewertungen (80)
- e***e (200)- Bewertung vom Käufer.Letzte 6 MonateBestätigter KaufSeller sent the wrong head cover. But made it right and sent me the correct one and just told me to keep the one he sent by accident. Good communication and saved me a lot of stress.Titleist 910D Golf Club Headcover For Drivers And Woods Oversized As Well (Nr. 127214815122)
- r***r (125)- Bewertung vom Käufer.Letzte 6 MonateBestätigter KaufThis seller packed the items nicely and shipped them promptly. They are very fragile but arrived safe and sound and nicer than described. Kudos to the seller.
- t***h (63)- Bewertung vom Käufer.Letzte 6 MonateBestätigter KaufGreat experience. Shipped fast. Packaged well and arrived as described.Vintage RCA Nipper Handheld HMV Harp Microphone "His Master's Voice" 1950s Rare (Nr. 127252324837)