A generalized learning algorithm of minor component

This paper proposes a generalized nonlinear minor component analysis algorithm. First, we will prove that with appropriate nonlinear functions the proposed algorithm can extract adaptively the minor component. Then we will discuss how to choose the related nonlinear functions so as to guarantee the desired convergence. Furthermore, we will show that all the other available minor component analysis algorithms are special cases of this proposed generalized algorithm. Finally, the complex-valued version of the proposed algorithm will be given in this paper for wider applications. In addition, this proposed minor component analysis algorithm can also be used to extract the principal component by simply reversing the sign of the corresponding terms