Neural Network Parallel Computing

AvYoshiyasu Takefuji

Inbunden, Engelska, 1992

Del i serien Springer International Series in Engineering and Computer Science

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Beskrivning

This introductory book is aimed not only for the novice reader, but also for experts in a variety of areas including parallel computing neural network computing, computer science, communications, graph theory, computer aided design for VLSI circuits, molecular biology, management science, and operations research. The aim of the book is to facilitate an understanding as to the uses of neural network models in real-world applications. It demonstrates the computational power of neural network computing by solving numerous problems such as N-queen, crossbar switch scheduling, four-colouring and k-colorability, graph planarization and channel routing, RNA secondary structure prediction, knight's tour, spare allocation, sorting and searching, and tiling.

Produktinformation

Utgivningsdatum:1992-01-31
Mått:155 x 235 x 21 mm
Vikt:553 g
Format:Inbunden
Språk:Engelska
Serie:Springer International Series in Engineering and Computer Science
Antal sidor:230
Upplaga:1992
Förlag:Kluwer Academic Publishers
ISBN:9780792391906

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Recensioner i media

' This is really the first good book on neural computing for optimization problems. Neural Network Parallel Computing is an excellent reference for researchers working on optimization problems, and for engineers searching for practical problem-solving methods. Overall, the book is a fascinating presentation of a very difficult problem of contemporary science. ' IEEE Parallel & Distributed Technology, Fall 1994 'However, the book does provide many useful algorithms and applications of neural networks. It is a worthwhile addition to a library of neutral network research.' Journal of systems and Control Engineering 206 1992

Innehållsförteckning

1. Neural Network Models and N-Queen Problems.- 2. Crossbar Switch Scheduling Problems.- 3. Four-Coloring and K-Colorability Problems.- 4. Graph Planarization Problems.- 5. Channel Routing Problems.- 6. RNA Secondary Structure Prediction.- 7. Knight’s Tour Problems.- 8. Spare Allocation Problems.- 9. Sorting and Searching.- 10. Tiling Problems.- 11. Silicon Neural Networks.- 12. Mathematical Background.- 13. Forthcoming Applications.- 14. Conjunctoids and Artificial Learning.