Hardware for Soft Computing and Soft Computing for Hardware

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, th...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Nedjah, Nadia (Συγγραφέας), Mourelle, Luiza de Macedo (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2014.
Σειρά:Studies in Computational Intelligence, 529
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Nedjah, Nadia.  |e author. 
245 1 0 |a Hardware for Soft Computing and Soft Computing for Hardware  |h [electronic resource] /  |c by Nadia Nedjah, Luiza de Macedo Mourelle. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2014. 
300 |a XII, 198 p. 124 illus.  |b online resource. 
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490 1 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 529 
520 |a 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, digital 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 problem 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. 
650 0 |a Engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Computer graphics. 
650 0 |a Computational intelligence. 
650 1 4 |a Engineering. 
650 2 4 |a Computational Intelligence. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Computer Graphics. 
700 1 |a Mourelle, Luiza de Macedo.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319031095 
830 0 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 529 
856 4 0 |u http://dx.doi.org/10.1007/978-3-319-03110-1  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)