Hardware for Soft Computing and Soft Computing for Hardware, Hardcover by Ned...-image

Hardware for Soft Computing and Soft Computing for Hardware, Hardcover by Ned...

$ 70.73

Subject Area: Computers, Technology & Engineering gtin13: 9783319031095 Publication Name: Hardware for Soft Computing and Soft Computing for Hardware Number of Pages: Xii, 198 Pages Item Width: 6.1 in Item Length: 9.3 in Language: English Format: Hardcover Item Weight: 156.6 Oz Publication Year: 2013 Author: Nadia Nedjah, Luiza De Macedo Mourelle ISBN: 9783319031095 Book Title: Hardware for Soft Computing and Soft Computing for Hardware Series: Studies in Computational Intelligence Ser. Item Height: 0.2 in Type: Textbook Publisher: Springer International Publishing A&G Subject: Computer Graphics, Programming / General, Engineering (General), Intelligence (Ai) & Semantics, Hardware / General, Data Processing

Description

Hardware for Soft Computing and Soft Computing for Hardware, Hardcover by Nedjah, Nadia (EDT); Mourelle, Luiza De Macedo (EDT), ISBN 3319031090, ISBN-13 9783319031095, Brand New, Free shipping in the US

Single and Multi-Objective Evolutionary Computation (MOEA), Genetic Algorithms (GAs), Artificial Neural Networks (ANNs), Fuzzy Controllers (FCs), Particle Swarm Optimization (PSO) and Ant colony Optimization (ACO) are becoming omnipresent in almost every intelligent system design. Unfortunately, the application of the majority of these techniques is complex and so requires a huge computational effort to yield useful and practical results. Therefore, dedicated hardware for evolutionary, neural and fuzzy computation is a key issue for designers. With the spread of reconfigurable hardware such as FPGAs, as well as analog hardware implementations of such computation become cost-effective. The idea behind this book is to offer a variety of hardware designs for soft computing techniques that can be embedded in any final product. Also, to introduce the successful application of soft computing technique to solve many hard problems encountered during the design of embedded hardware designs. Reconfigurable embedded designs for GAs, ANNs, FCs and PSO are presented and evaluated. Also, the application of quantum-based evolutionary computation and multi-objective evolutionary computation as well as ACO are applied to solve hard problems related to circuit synthesis, IP assignment, mapping and routing of applications on Network-On-Chip infrastructures.

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