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About this product
- DescriptionNeural Network Parallel Computing is the first book available to the professional market on neural network computing for optimization problems. This introductory book is t only for the vice reader, but 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 goal of the book is to facilitate an understanding as to the uses of neural network models in real-world applications. Neural Network Parallel Computing presents a major breakthrough in science and a variety of engineering fields. The computational power of neural network computing is demonstrated by solving numerous problems such as N-queen, crossbar switch scheduling, four-coloring and k-colorability, graph planarization and channel routing, RNA secondary structure prediction, knight's tour, spare allocation, sorting and searching, and tiling. Neural Network Parallel Computing is an excellent reference for researchers in all areas covered by the book. Furthermore, the text may be used in a senior or graduate level course on the topic.
- Author(s)Yoshiyasu Takefuji
- PublisherSpringer-Verlag New York Inc.
- Date of Publication22/12/2012
- Series TitleThe Springer International Series in Engineering and Computer Science
- Series Part/Volume Number164
- Place of PublicationNew York, NY
- Country of PublicationUnited States
- ImprintSpringer-Verlag New York Inc.
- Content Notebiography
- Weight402 g
- Width160 mm
- Height240 mm
- Spine13 mm
- Edition StatementSoftcover reprint of the original 1st ed. 1992
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