Application of stochastic adding A/D conversion in adaptive measurement and fuzzyfication

Abstract

Stochastic adding A/D conversion (SAADK) represents a method of measurement (or classification) which naturally can replace process of fuzzyfication of input quantities. The stochastic adding A/D conversion is an adaptive process. The accuracy of measurements using SAADK is proportional to the square root from measurement time interval, i.e. for the twice greater accuracy, the measurement time interval must be four times longer. The adaptivity of the accuracy of measurement and the possibility of direct fuzzyfication decreases hardware complexity and increases the speed and reliability. The main goal of this research work is to confirm that the fuzzy logic and SAADK are complementary, and to suggest the method of their combined application.