Titlebook: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems; M.C. Bhuvaneswari Book 2015 Springer

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Der Strategisch-Behaviorale Ansatz,uch as genetic algorithms (GAs) and particle swarm optimization (PSO) are ideal candidates for DSE since they are capable of generating a population of trade-off solutions in a single run. The application of multi-objective GA and PSO approaches for optimization of power, area, and delay during data

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Der Strategisch-Behaviorale Ansatz,ardware accelerators). Furthermore, as the performance of particle swarm optimization is known for being highly dependent on its parametric variables, in the proposed methodology, sensitivity analysis has been executed to tune the baseline parametric setting before performing the actual exploration

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Embodiment, Emotion, and Cognitionthe fault-dropping phase and hence very good reductions in transition activity are achieved. Tests are generated for scan versions of ISCAS’89, ISCAS’85, and ITC’99 benchmark circuits. Experimental results demonstrate that NSGA-II-based fault simulator gives higher fault coverage, reduced transition

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

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Book 2015e 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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Design Space Exploration for Scheduling and Allocation in High Level Synthesis of Datapaths,uch as genetic algorithms (GAs) and particle swarm optimization (PSO) are ideal candidates for DSE since they are capable of generating a population of trade-off solutions in a single run. The application of multi-objective GA and PSO approaches for optimization of power, area, and delay during data