New Approach of Test for DAC Using Fuzzy Neural Networks

Due to the existence of analogue signals, testing the mixed signal circuits is a complex and complicated one. D/A converters are one of the most important types of these circuits. In this paper, a method is presented to determine the points where faults are occurred in a 4-bit resistive ladder D/A converter, using fuzzy rules. For the purpose of implementing fuzzy rules, neural networks have been utilized. Also for improvement the fault coverage of this test method the LVQ neural network has been used. Firstly, the circuit has been simulated using ORCAD9 and then training patterns have been elicited. Continually, network simulation and training have been implemented via MATLAB6.1TM .