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Performance Study of Harmony Search Algorithm for Analog Circuit Sizing

机译:模拟电路尺寸和谐搜索算法性能研究

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Automation in nominal design of analog circuits considerably reduces the overall time to market of mixed-mode ICs. Application of meta-heuristic optimization algorithms with simulator level fitness evaluation for circuit sizing is a popular automation approach. In this work, with the same approach, we investigate the performance of Harmony Search (HS) algorithm. HS is a relatively new meta-heuristic inspired from musical process, in which population represents memory of a group of musicians, that searches for a perfect state of harmony. Performance of HS is compared with Differential Evolution (DE) algorithm for design of a 180nm CMOS process based Folded Cascode Operational Trans-conductance Amplifier (FCOTA) with continuous time common mode feedback. Results show that, at initial period of iterations, HS converges quickly but fails to converge to the global optimum as compared to DE algorithm.
机译:在模拟电路的标称设计中自动化显着降低了混合模式IC的整体时间。元启发式优化算法在电路尺寸下采用模拟器级适应性评估的应用是一种流行的自动化方法。在这项工作中,具有相同的方法,我们调查和声搜索(HS)算法的性能。 HS是一种来自音乐流程的相对较新的荟萃启发式,其中人口代表了一群音乐家的记忆,从而寻求完美的和谐状态。将HS的性能与差分演进(DE)算法进行比较,用于设计基于180nm CMOS工艺的折叠式级码操作传输放大器(FCOTA),连续时间共模反馈。结果表明,在初始迭代期间,HS将很快收敛但不能与DE算法相比收敛到全局最佳。

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