Introduction - If you have any usage issues, please Google them yourself
This network uses gaussian membership functions with two free parameters: mean and variance The total number of these parameters is M* N, where M is the number of rules, N is the number of inputs There is a hidden set of parameters of tsk..-functions which perform a linear convolution of fuzzy inference outputs with a set of coefficiants. Total number of these parameters is M* (N+1). So the total amount of adjusted parameters is 2* M* N+ M.