Test Set Optimization Based on Intelligent Hybrid Algorithm

Author

Wu, GuoQing ; Ma, Sasa ; Zhao, ShouWei

Author_Institution

Sci. & Tech. Inst. of Inf., Beijing Inst. of Technol.

fYear

2006

fDate

23-26 Oct. 2006

Firstpage

2138

Lastpage

2141

Abstract

The optimization of digital circuit test set can reduce VLSI test cost by compacting test vectors and cutting down test time. Ant colony optimization (ACO) and particle swarm optimization (PSO) are the novel bionics optimization algorithms on the basis of iteration. Utilizing intelligent hybrid optimization algorithm of ACO and PSO can delete redundancy of test vectors so as to solve the optimization problem for test sets. And it is proved the feasibility of this algorithm through the experiment

Keywords

VLSI; digital integrated circuits; integrated circuit testing; particle swarm optimisation; VLSI test; ant colony optimization; bionics optimization; digital circuit test set; intelligent hybrid optimization; particle swarm optimization; test set optimization; test vectors; Ant colony optimization; Circuit faults; Circuit testing; Cost function; Digital circuits; Educational institutions; Integrated circuit testing; Particle swarm optimization; Redundancy; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Solid-State and Integrated Circuit Technology, 2006. ICSICT '06. 8th International Conference on

Conference_Location

Shanghai

Print_ISBN

1-4244-0160-7

Electronic_ISBN

1-4244-0161-5

Type

conf

DOI

10.1109/ICSICT.2006.306662

Filename

4098649