Year: 2025
Type: article
Abstract: Particle swarm optimization (PSO) is a computational method used for solving different types of optimization problems.The social behaviors of fish schooling and flocks of birds mostly influence the PSO.PSO uses a collection of particles to explore the search space and locate the best possible solution.Each particle updates its position depending upon experience of itself or from neighboring particles, aiming to find the best solution in terms of the objective function being optimized.Crazinessbased Particle Swarm Optimization (CRPSO) is an advanced variation of the standard Particle Swarm Optimization (PSO) algorithm.CRPSO introduces a "craziness" factor to enhance the diversity of the swarm and prevent premature convergence to local optima.This paper deals with the design of a CMOS differential amplifier circuit with a current mirror load using CRPSO algorithm.The optimized sizes of the transistors are obtained using CRPSO to decrease the overall transistor area while meeting design limitations.The results achieved using the CRPSO are validated in the SPICE.The simulation result shows the superiority of CRPSO in the design of differential amplifier.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4412763846