遗传算法在基于fgmos的CMOS-MEMS换能器设计中的应用及其适用性

B. Granados-Rojas, M. Reyes-Barranca, L. M. Flores-Nava, G. Abarca-Jimenez, S. Mendoza-Acevedo, Y. E. González-Navarro
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引用次数: 1

摘要

在这项工作中,为了提高对CMOS - MEMS传感器器件设计与一组启发式技术(称为遗传算法)之间兼容性的认识,进行了初步的方法和需求概述。众所周知,遗传算法主要应用于多变量函数优化领域,这种最简单的迭代过程可以作为一种工具,用于已知变量和限制条件的集成CMOS器件和技术的自动化设计。基于fgmos的器件以及MEMS结构在嵌入单芯片平台(CMOS - MEMS技术)时,预计将符合一套机械和电气性能的设计规则,从而更容易编码和解码变量,以便在离散的总是正的基础上用于遗传算法。在这种方法中,忽略了寄生和过程分辨率相关的问题,并鼓励基于更详细的建模和参数限制的进一步分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application and Resulting Suitability of a Genetic Algorithm in the Design of FGMOS-based CMOS-MEMS Transducers
In this work an initial approach and requirements overview is performed in order to promote awareness on the compatibility between CMOS – MEMS sensor devices design and the group of heuristic techniques known as genetic algorithms. As might be known, genetic algorithms (GAs) main application is in the field of multivariable functions optimization and this kind of iterative procedures in their simplest forms may be suitable to serve as a tool in the automation of design of integrated CMOS devices and technologies where the variables and restrictions are known. FGMOS-based devices along with MEMS structures when embedded in a single-chip platform (CMOS – MEMS technology) are expected to be in compliance with a set of design rules for both their mechanical and electrical properties, making easier to code and decode variables for their use in a GA in a discrete always-positive basis. In this approach, parasitic and process-resolution-related issues are neglected and further analysis based in a more detailed modeling and parameter restrictions is encouraged.
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