Center of slice area average defuzzifier for digital implementations of fuzzy systems

Fuzzy hardware has turned to be the choice to reach high speed inference rates. There are two forms to represent membership values universe: first case is when floating point numbers are used, second case is when integer universe is used, on this case, membership universe belong to interval of integers [0, m], where m is an integer that is on dependence of number of bits used according to resolution demands. This case is fully compatible with digital computers because floating point operations consume much more time and resources than integer operations. This work presents a new method for defuzzification which is designed to work with α-level represented membership functions using integer universe, it is shown that number of instructions executed are less than for most used COG. Fewer processing time and less resources consumed are obtained presenting simulation results.