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

Nonfiction, Science & Nature, Technology, Electronics, Circuits, Computers, Advanced Computing, Artificial Intelligence
Cover of the book Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems by , Springer India
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9788132219583
Publisher: Springer India Publication: August 20, 2014
Imprint: Springer Language: English
Author:
ISBN: 9788132219583
Publisher: Springer India
Publication: August 20, 2014
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer India

Cover of the book The Rise of Acid Reflux in Asia by
Cover of the book ICoRD'13 by
Cover of the book Advancements of Medical Electronics by
Cover of the book Marker-Assisted Plant Breeding: Principles and Practices by
Cover of the book Functional Instability or Paradigm Shift? by
Cover of the book Systems Biology Application in Synthetic Biology by
Cover of the book Data Analysis in Management with SPSS Software by
Cover of the book Plant Tissue Culture: An Introductory Text by
Cover of the book Ovarian Stimulation Protocols by
Cover of the book Human Capital and Development by
Cover of the book Recent Advances in Lichenology by
Cover of the book ZnO Nanocrystals and Allied Materials by
Cover of the book Biotechnology for Environmental Management and Resource Recovery by
Cover of the book Clinical Pathways in Emergency Medicine by
Cover of the book Proceedings of International Conference on Soft Computing Techniques and Engineering Application by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy