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Optimization of CMOS Current Mirror Load-based Differential Amplifier using Hybrid Cuckoo Search and Particle Swarm Optimization Algorithm

Pankaj P. Prajapati, Mihir V. Shah


Optimization of CMOS based analog circuits is becoming a practical solution for complex analog modules. There are number of evolutionary algorithms presented to optimize the analog circuits in different reported literatures. During optimization process, the optimal result may not be obtained with only individual algorithm or requires a more time. Therefore the hybrid algorithm of two or more algorithms is more effective method to obtain the goal. The Particle Swarm Optimization (PSO) algorithm is easy to implement and has good convergence speed. However, The Cuckoo Search (CS) algorithm has better skill to catch a global optimal result. A hybrid algorithm of CS and PSO (CSPSO) is developed to get the gains of the CS and PSO algorithms. In this work, CSPSO algorithm is tested to design the CMOS current mirror load-based differential amplifier (DA) with 180 nm CMOS technology parameters. The hybrid CSPSO algorithm is implemented with C language and interfaced with Ng-spice circuit simulator using script file. In this work, the CSPSO algorithm is used as a searching tool for transistor sizing and Ng-spice has been used as a fitness creator. The experimental simulation results show that the hybrid CSPSO algorithm outperforms with PSO and CS algorithms.  


Cite this Article

Pankaj P. Prajapati, Mihir V. Shah, Optimization of CMOS Current Mirror Load-based Differential Amplifier using Hybrid Cuckoo Search and Particle Swarm Optimization Algorithm. Journal of Artificial Intelligence Research & Advances. 2018; 5(3): 71–78p.


Evolutionary Algorithm, Cuckoo Search Algorithm, Particle Swarm Optimization Algorithm, Hybrid Algorithm, Optimization

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