๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Evolutionary Algorithms for Embedded System Design

โœ Scribed by Joachim Wegener (auth.), Rolf Drechsler, Nicole Drechsler (eds.)


Publisher
Springer US
Year
2003
Tongue
English
Leaves
201
Series
Genetic Algorithms and Evolutionary Computation 10
Edition
1
Category
Library

โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.

โœฆ Synopsis


Evolutionary Algorithms for Embedded System Design describes how Evolutionary Algorithm (EA) concepts can be applied to circuit and system design - an area where time-to-market demands are critical. EAs create an interesting alternative to other approaches since they can be scaled with the problem size and can be easily run on parallel computer systems. This book presents several successful EA techniques and shows how they can be applied at different levels of the design process. Starting on a high-level abstraction, where software components are dominant, several optimization steps are demonstrated, including DSP code optimization and test generation. Throughout the book, EAs are tested on real-world applications and on large problem instances. For each application the main criteria for the successful application in the corresponding domain are discussed. In addition, contributions from leading international researchers provide the reader with a variety of perspectives, including a special focus on the combination of EAs with problem specific heuristics.

Evolutionary Algorithms for Embedded System Design is an excellent reference for both practitioners working in the area of circuit and system design and for researchers in the field of evolutionary concepts.

โœฆ Table of Contents


Front Matter....Pages i-xxviii
Evolutionary Testing of Embedded Systems....Pages 1-33
Genetic Algorithm Based DSP Code Optimization....Pages 35-62
Hierarchical Synthesis of Embedded Systems Using Evolutionary Algorithms....Pages 63-104
Functional Test Generation....Pages 105-142
Built-In Self Test of Sequential Circuits....Pages 143-173
Back Matter....Pages 175-177

โœฆ Subjects


Circuits and Systems; Artificial Intelligence (incl. Robotics); Computer-Aided Engineering (CAD, CAE) and Design; Optimization; Electrical Engineering


๐Ÿ“œ SIMILAR VOLUMES


Application of Evolutionary Algorithms f
โœ M.C. Bhuvaneswari (eds.) ๐Ÿ“‚ Library ๐Ÿ“… 2015 ๐Ÿ› Springer India ๐ŸŒ English

<p>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 mod

Designing Evolutionary Algorithms for Dy
โœ Ronald W. Morrison (auth.) ๐Ÿ“‚ Library ๐Ÿ“… 2004 ๐Ÿ› Springer-Verlag Berlin Heidelberg ๐ŸŒ English

<p>The robust capability of evolutionary algorithms (EAs) to find solutions to difficult problems has permitted them to become popular as optimization and search techniques for many industries. Despite the success of EAs, the resultant solutions are often fragile and prone to failure when the proble

Flow Design for Embedded Systems
โœ Barry Kauler ๐Ÿ“‚ Library ๐Ÿ“… 1999 ๐Ÿ› R & D Books ๐ŸŒ English

Barry Kauler's Flow Design is a technique for applying object methods to embedded real-time systems, and for designing powerful objects for real-time systems. The companion disk to this text provides both GOOFEE and TERSE, an interrupt drive operating system.

Evolutionary Data Clustering: Algorithms
โœ Ibrahim Aljarah (editor), Hossam Faris (editor), Seyedali Mirjalili (editor) ๐Ÿ“‚ Library ๐Ÿ“… 2021 ๐Ÿ› Springer ๐ŸŒ English

<span>This book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the boo