Evolvable Hardware (Genetic Programming Vol.11) (2006. 250 p. w. 30 ill. 23,5 cm)

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Evolvable Hardware (Genetic Programming Vol.11) (2006. 250 p. w. 30 ill. 23,5 cm)

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  • 製本 Hardcover:ハードカバー版/ページ数 250 p./サイズ 30 illus.
  • 言語 ENG
  • 商品コード 9780387243863

基本説明

Provides the basics of reconfigurable devices so that readers will be fully prepared to understand what EHW is, why it is necessary and how it is designed.

Full Description

Evolvable hardware (EHW) refers to hardware whose architecture/structure and functions change dynamically and autonomously in order to improve its performance in carrying out tasks. The emergence of this field has been profoundly influenced by the progress in reconfigurable hardware and evolutionary computation. Traditional hardware can be inflexible - the structure and its functions are often impossible to change once it is created. However, most real world problems are not fixed - they change with time. In order to deal with these problems efficiently and effectively, different hardware structures are necessary. EHW provides an ideal approach to make hardware "soft" by adapting the structure to a problem dynamically. The contributions in this book provide the basics of reconfigurable devices so that readers will be fully prepared to understand what EHW is, why it is necessary and how it is designed. The book also discusses the leading research in digital, analog and mechanical EHW.

Contents

to Evolvable Hardware.- EHW Applied to Image Data Compression.- A GA Hardware Engine and Its Applications.- Post-Fabrication Clock-Timing Adjustment Using Genetic Algorithms.- Bio-Inspired Computing Machines with Artificial Division and Differentiation.- The Poetic Hardware Device: Assistance for Evolution, Development and Learning.- Evolvable Analog LSI.- Reconfigurable Electronics for Extreme Environments.- Characterization and Synthesis of Circuits at Extreme Low Temperatures.- Human-Competitive Evolvable Hardware Created by Means of Genetic Programming.- Evolvable Optical Systems.- Hardware Platforms for Electrostatic Tuning of Mems Gyroscope Using Nature-Inspired Computation.

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