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Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
Kategorie	Beschreibung
036a	XB-IN
037b	eng
087q	978-81-322-1957-6
100	Bhuvaneswari, M.C.
331	Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
410	New Delhi ; s.l.
412	Springer India
425	2015
425a	2015
433	Online-Ressource (XI, 174 p. 63 illus., 8 illus. in color, online resource)
451b	SpringerLink. Bücher
501	Description based upon print version of record
517	Introduction to Multi-Objective Evolutionary AlgorithmsHardware/Software Partitioning for Embedded Systems -- Circuit Partitioning for VLSI Layout -- Design of Operational Amplifier -- Design Space Exploration for Scheduling and Allocation in High Level Synthesis of Datapaths -- Design Space Exploration of Datapath (Architecture) in High Level Synthesis for Computation Intensive Applications -- Design Flow from Algorithm to RTL using Evolutionary Exploration Approach -- Crosstalk Delay Fault Test Generation -- Scheduling in Heterogeneous Distributed Systems. .
527	Druckausg.ISBN: 978-813-2219-57-6
540a	ISBN 978-81-322-1958-3
700	\|TJFC
700	\|TEC008010
700	\|*68-06
700	\|68T20
700	\|90C29
700	\|90C90
700	\|00B15
700b	\|621.3815
700c	\|TK7888.4
750	Introduction to Multi-Objective Evolutionary Algorithms -- Hardware/Software Partitioning for Embedded Systems -- Circuit Partitioning for VLSI Layout -- Design of Operational Amplifier -- Design Space Exploration for Scheduling and Allocation in High Level Synthesis of Datapaths -- Design Space Exploration of Datapath (Architecture) in High Level Synthesis for Computation Intensive Applications -- Design Flow from Algorithm to RTL using Evolutionary Exploration Approach -- Crosstalk Delay Fault Test Generation -- Scheduling in Heterogeneous Distributed Systems. .
753	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 multi-objective GA and PSO in a simple and easily understandable way that will appeal to introductory readers.
012	416042511
081	Bhuvaneswari, M.C.: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
100	Springer E-Book
125a	Elektronischer Volltext - Campuslizenz
655e	$uhttp://dx.doi.org/10.1007/978-81-322-1958-3