Given n arbitrarily different training samples are (x, t) = {(Xi, Ti) |1 ≤ I ≤ n}, where x is the input sample matrix and t is the expected output matrix corresponding to X,
Let n arbitrary different training samples be (X,T)={(Xi ,Ti )|1≤i≤N}, where x is the input sample matrix and t is the expected output matrix corresponding to x,