Optimizing Method for Analog Circuit Design Using Adaptive Immune Genetic Algorithm

The design of an analog circuit is so complex that much time is required. To improve the speed and efficiency of evolutionary hardware design, this paper presented an adaptive immune genetic algorithm (AIGA). The optimization of the analog circuit is the optimization of multi-dimensional parameters, and the trade-off of all parameters. The genetic algorithm is suitable for the optimization of the multi-dimensional parameters and the immune algorithm is suitable for the improvement of diversity. So AIGA can improve the searching ability, adaptability and the convergence speed. As an example, the optimization of parameters of a low-pass filter is presented. From simulation results, we confirm that the proposed method is suitable for the optimizing of the analog circuit.

I. Introduction

Recently, automated analog circuit design techniques have been proposed. Analog circuits are of great importance in electronic system design since the world is fundamentally analog in nature. Many analog circuit designs suffer from long design time, high complexity, high cost and requires highly skilled designers. Consequently, automated synthesis methodologies for analog circuits have received much attention.