Diagnosis of soft faults in analog integrated circuits based on fractional correlation

Abstract

Aiming at the problem of diagnosing soft faults in analog integrated circuits, an approach based on fractional correlation is proposed. First, the Volterra series of the circuit under test (CUT) decomposed by the fractional wavelet packet are used to calculate the fractional correlation functions. Then, the calculated fractional correlation functions are used to form the fault signatures of the CUT. By comparing the fault signatures, the different soft faulty conditions of the CUT are identified and the faults are located. Simulations of benchmark circuits illustrate the proposed method and validate its effectiveness in diagnosing soft faults in analog integrated circuits.