Title :
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.
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;
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
DOI :
10.1109/ICSICT.2006.306662
