Analysis of circuits containing nonlinear elements using neural networks and genetic algorithm

Abstract

The use of a neural network model to analyze electronic circuits is a promising new technique in the field of circuit analysis. This new technique allows the electronic circuits to be analyzed without the need to solve the physical equations describing the circuit. This paper introduces a novel technique to solve electronic circuits that contain linear and non-linear elements. The non-linear elements are chosen to be PN junction diodes in the forward bias condition at different operating temperatures. The technique is based on the neural network and the genetic algorithm. The neural network is used to model the PN junction diode with the help of the genetic algorithm as a learning tool. Then, the genetic algorithm is used to search the solution space domain to find the proper solutions of the electronic circuits. The proposed technique is faster due to the use of parallel operation from the both neural networks and the genetic algorithm. Moreover, the results are very accurate.