Test Generation Algorithm Based on SVM with Compressing Sample Space Methods
Abstract: Test generation
algorithm based on the SVM (support vector machine) generates test signals derived
from the sample space of the output responses of the analog DUT. When the
responses of thenormal circuits are similar to those of the faulty circuits
(i.e., the latter have only small parametric faults), the sample space is mixed
a d traditional algorithms have difficulty distinguishing the two groups. However,
the SVM provides an effective result. The sample space contains redundant data,
because successive impulse-response
samples may get quite close. The redundancy will waste the needless computational
load. So we propose three difference methods to compress the sample space. The compressing
sample space methods are Equidistant compressional method, k-nearest neighbors
method and maximal difference method. Numerical experiments prove that maximal
difference method can ensure the precision of the test generation.
Author: Ting Long, Jiang Shiqi,
Hang Luo
Journal Code: jptkomputergg150101
