Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems. (Record no. 865910)

001 - CONTROL NUMBER
control field EBL1802682
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
additional material characteristics m d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr -n---------
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 141119s2014||||||| s|||||||||||eng|d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788132219583
Terms of availability 129 (NL)
035 ## - SYSTEM CONTROL NUMBER
System control number (AU-PeEL)1802682
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)894170382
040 ## - CATALOGING SOURCE
Original cataloging agency AU-PeEL
Language of cataloging eng
Transcribing agency AU-PeEL
Modifying agency AU-PeEL
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TK7874.75
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
-- 621.39/5
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (OCLC)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) TK7874.75
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Bhuvaneswari, M.C.
245 10 - TITLE STATEMENT
Title Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Dordrecht :
Name of publisher, distributor, etc Springer,
Date of publication, distribution, etc 2014.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (181 p.)
490 0# - SERIES STATEMENT
Series statement eBooks on Demand
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Preface; Organization of the Book; Acknowledgements; Contents; About the Editor; Chapter 1: Introduction to Multi-objective Evolutionary Algorithms; 1.1 Introduction; 1.2 Multi-objective Optimization Problem; 1.3 Why Evolutionary Algorithms?; 1.4 Multi-objective Evolutionary Algorithms; 1.5 Genetic Algorithm; 1.6 Multi-objective Genetic Algorithm; 1.6.1 Weighted Sum Genetic Algorithm (WSGA); 1.6.2 Nondominated Sorting Genetic Algorithm II (NSGA-II); 1.6.2.1 Nondominated Sorting; 1.6.2.2 Crowding Distance; 1.6.2.3 Crowded Tournament Selection; 1.6.3 NSGA-II with Controlled Elitism (NSGA-II-CE)
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 1.6.4 Hybrid NSGA-II with Pareto Hill Climbing (NSGA-II-PHC)1.7 Particle Swarm Optimization; 1.8 Multi-objective Particle Swarm Optimization; 1.8.1 Weighted Sum Particle Swarm Optimization; 1.8.2 Nondominated Sorting Particle Swarm Optimization (NSPSO); 1.8.3 Adaptive NSPSO (ANSPSO); 1.8.3.1 Learning Factors; 1.8.3.2 Inertia Weight; 1.8.4 Hybrid NSPSO with Pareto Hill Climbing (NSPSO-PHC); References; Chapter 2: Hardware/Software Partitioning for Embedded Systems; 2.1 Introduction; 2.2 Prior Work on HW/SW Partitioning; 2.3 Target Architecture; 2.4 Input Model; 2.5 Objective Function
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 2.6 Encoding Procedure2.7 Performance Metric Evaluation; 2.7.1 Metrics Evaluating Closeness to True Pareto-Optimal Front; 2.7.1.1 Error Ratio (ER); 2.7.1.2 Generational Distance (GD); 2.7.1.3 Maximum Pareto-Optimal Front Error (MFE); 2.7.2 Metrics Evaluating Diversity among Nondominated Solutions; 2.7.2.1 Spacing (S); 2.7.2.2 Spread (Delta); 2.7.2.3 Weighted Metric (W); 2.8 Experimental Results; 2.9 Summary; References; Chapter 3: Circuit Partitioning for VLSI Layout; 3.1 Introduction; 3.2 Prior Work on Circuit Partitioning; 3.3 Illustration of Circuit Bipartitioning Problem
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 3.4 Circuit Bipartitioning Using Multi-objective Optimization Algorithms3.4.1 Encoding Procedure; 3.4.2 Fitness Function Formulation; 3.5 Experimental Results; 3.6 Summary; References; Chapter 4: Design of Operational Amplifier; 4.1 Problem Definition; 4.2 Operational Amplifier Design; 4.2.1 Miller OTA Architecture; 4.2.1.1 Computation of Objectives; 4.2.2 Folded Cascode Amplifier Architecture; 4.2.2.1 Computation of Objectives; 4.3 Multi-objective Genetic Algorithm for Operational Amplifier Design; 4.3.1 Circuit Representation for Miller OTA
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 4.3.2 Circuit Representation for Folded Cascode OpAmp4.3.3 WSGA-Based OpAmp Design; 4.3.3.1 Fitness Function; 4.3.4 Experimental Results of WSGA Method; 4.3.4.1 Experimental Results for Folded Cascode OpAmp; 4.4 Operational Amplifier Design Using NSGA-II; 4.4.1 Multi-objective Fitness Function; 4.4.2 Simulation Results Obtained Using NSGA-II Algorithm; 4.5 Summary; References; Chapter 5: Design Space Exploration for Scheduling and Allocation in High Level Synthesis of Datapaths; 5.1 Introduction; 5.2 Datapath Synthesis; 5.3 Related Work
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 5.4 Multi-objective Evolutionary Approaches to Datapath Scheduling and Allocation
520 ## - SUMMARY, ETC.
Summary, etc 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 ampl
588 ## -
-- Description based upon print version of record.
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Electronic digital computers -- Circuits -- Congresses.
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Integrated circuits -- Very large scale integration -- Design and construction -- Congresses.
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Signal processing -- Digital techniques -- Congresses.
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Soft computing -- Congresses.
655 #0 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Print version:
Main entry heading Bhuvaneswari, M.C.
Title Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
Place, publisher, and date of publication Dordrecht : Springer,c2014
International Standard Book Number 9788132219576
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://uttyler.eblib.com/patron/FullRecord.aspx?p=1802682">http://uttyler.eblib.com/patron/FullRecord.aspx?p=1802682</a>
Link text Click here to view this ebook.
901 ## - LOCAL DATA ELEMENT A, LDA (RLIN)
Platform EBL
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Electronic Book
Source of classification or shelving scheme
Holdings
Withdrawn status Lost item Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Uniform Resource Identifier Price effective from Koha item type
          UT Tyler Online UT Tyler Online Online 11/24/2014   TK7874.75 EBL1802682 11/24/2014 http://uttyler.eblib.com/patron/FullRecord.aspx?p=1802682 11/24/2014 Electronic Book