Analog Circuit Complementary Optimization Based on Evolutionary Algorithms and Artificial Neural Network

Subject Areas : Communication

Behzad Rajabi ¹ , Farhad Razaghian ²

1 - Dept. Electrical Eng., South Tehran Branch, Islamic Azad University, Tehran, Iran.
2 - Dept. Electrical Eng., South Tehran Branch,Islamic Azad University

Received: 2017-11-13 Accepted : 2018-03-13 Published : 2018-03-01

Keywords: Cost function, Analog circuit, Evolutionary algorithm optimization, Multi-Layer Perceptron Neural network,

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.