Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

Name: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
Brand: Springer, India, Private Ltd
SKU: 9788132235392
Price: 105.11 EUR
Availability: InStock

Автор: M. C. Bhuvaneswari

Език:

Корици: С меки корици

Издател: Springer, India, Private Ltd

Наличност: Външен склад

Изпращаме след 5-8 дни

105.11 € 205.57 лв

This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle...

Информация за книгата

Автор

M. C. Bhuvaneswari

Език

Английски език

Корици

Книга - С меки корици

Издадена

2016

страници

174

EAN

9788132235392

ISBN

8132235398

Enbook ID

14227678

Издател

Springer, India, Private Ltd

Теглоt

2934

Размери

155 x 235 x 10

Пълно описание

This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation and operators like crossover, mutation, etc, can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field of VLSI and embedded system design. The book introduces the multi-objective GA and PSO in a simple and easily understandable way that will appeal to introductory readers.

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Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

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