Analog Circuit Complementary Optimization Based on Evolutionary Algorithms and Artificial Neural Network
Publish place: Signal Processing and Renewable Energy، Vol: 2، Issue: 1
Publish Year: 1397
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_SPRE-2-1_003
تاریخ نمایه سازی: 23 تیر 1398
Abstract:
In analog circuit optimization, obtaining optimal point that can satisfy various kinds of specifications is posed as goal of design. Utilization of evolutionary algorithms was introduced as a useful method but speed of convergence and ensure to access optimal point are these method most challenges. In this paper the Multi-Layer Perceptron (MLP) artificial neural network is applied to access the suitable point appropriate different specifications values of analog circuit. This point used in optimization algorithm to find reliable response. Neural network itself is trained by training database is collected during initial optimization process. The link of HSPICE and MATLAB is used for circuit simulation and evaluation during the process.
Keywords:
Analog circuit , Evolutionary algorithm optimization , Cost function , Multi-Layer Perceptron Neural network
Authors
Behzad Rajabi
Dept. Electrical Eng., South Tehran Branch, Islamic Azad University, Tehran, Iran.
Farhad Razaghian
Dept. Electrical Eng., South Tehran Branch,Islamic Azad University