Synthesis of Time-to-Amplitude Converter by Mean CoeVolution with Adaptive Parameters

Yerbol A Sapargaliyev,Tatiana G Kalganova

doi:10.4236/jsea.2011.48052

Yerbol A Sapargaliyev, Tatiana G Kalganova

Open Access

https://doi.org/10.4236/jsea.2011.48052

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Abstract

The challenging task to synthesize automatically a time-to-amplitude converter, which unites by its functionality several digital circuits, has been successfully solved with the help of a novel methodology. The proposed approach is based on a paradigm according to which the substructures are regarded as additional mutation types and when ranged with other mutations form a new adaptive individual-level mutation technique. This mutation approach led to the discovery of an original coevolution strategy that is characterized by very low selection rates. Parallel island-model evolution has been running in a hybrid competitive-cooperative interaction throughout two incremental stages. The adaptive population size is applied for synchronization of the parallel evolutions.

Highlights

The analog circuit is much more difficult to design than the digital one due to the complex and knowledge-intensive nature of the analog electronics
We suggested seven cases of coupled signals corresponding to distances 0.4, 2, 10, 30, 45, 65, and 95 km to tackle the problem of generalization
For time interval meter circuit (TIMC), initially we have tried to evolve the whole circuit at once without exploiting the task decomposition, but the evolution has failed to converge toward the acceptable solution

Summary

Introduction

The analog circuit is much more difficult to design than the digital one due to the complex and knowledge-intensive nature of the analog electronics. Without an automated synthesis methodology, analog circuit design has suffered from long design time, high complexity and cost, and requires large experience. Automated synthesis methodologies for analog circuits have received much attention. Evolutionary strategy (ES) has been found to be one of the most powerful evolutionary algorithms (EA) when applied toward the synthesis of electronic circuits [1,2,3,4]. In the area of analog circuit synthesis, the number of publications on ES applications converges are few in comparison with those of genetic algorithms and genetic programming

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