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Autor(en): 
  • Nadia Nedjah
  • Luiza De Macedo Mourelle
  • Hardware for Soft Computing and Soft Computing for Hardware 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  August 2016  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Artificial Intelligence / B / Computational Intelligence / Computational Intelligence;Hardware;Soft Computing / Computer Graphics / engineering / Graphics programming
    ISBN:  9783319378749 
    EAN-Code: 
    9783319378749 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #529 - Studies in Computational Intelligence  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  3285 gr 
    Seiten:  198 
    Illustration:  XII, 198 p. 124 illus., schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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 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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