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Springer Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques: 294 (Studies in Computational Intelligence, 294)

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Description

Transistor-level design for complex mixed-signal systems-on-chip remains difficult to automate. This book shows how a modified genetic algorithm kernel can improve efficiency in the analog IC design cycle and includes a worked example of the method. From the Back Cover The microelectronics market trends present an ever-increasing level of complexity with special emphasis on the production of complex mixed-signal systems-on-chip. Strict economic and design pressures have driven the development of new methods to automate the analog design process. However, and despite some significant research efforts, the essential act of design at the transistor level is still performed by the trial and error interaction between the designer and the simulator. This book presents a new design automation methodology based on a modified genetic algorithm kernel, in order to improve efficiency on the analog IC design cycle. The proposed approach combines a robust optimization with corner analysis, machine learning techniques and distributed processing capability able to deal with multi-objective and constrained optimization problems. The resulting optimization tool and the improvement in design productivity is demonstrated for the design of CMOS operational amplifiers.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
28 May 2012
Listed Since
19 May 2012

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