To overcome the disadvantage of linear dissimilarity analysis (DISSIM) when monitoring nonlinear processes, a kernel dissimilarity analysis algorithm, termed KDISSIM here, is presented, which is the nonlinear version of DISSIM algorithm. A kernel dissimilarity index is introduced to quantitatively evaluate the differences between nonlinear data distribution structures, which can reflect the cha...
