Signals from multi-sensor systems are often mixtures of (statistically) independent sources by unknown mixing method. Blind source separation(BSS) and independent component analysis(ICA) are the methods to identify/recover the channels and the sources. BSS/ICA of nonlinear mixing models are difficult problems. For instance, the post-nonlinear model has been studied by several authors. It is noticed that in most cases, the proposed models are always with an invertible mixing. According to this fact there is an interesting question: how about the situation of the non-invertible non-linear mixing in BSS or ICA A new simple non-linear mixing model is proposed with a kind of non-invertible mixing, the folding mixing, and method to identify its channel, blindly. Signals from multi-sensor systems are often mixtures of (statistically) independent sources by unknown mixing method. Blind source separation (BSS) and independent component analysis (ICA) are the methods to identify / recover the channels and the sources. BSS / ICA of For instance, the post-nonlinear model has been studied by several authors. It is noticed that in most cases, the proposed models are always with an invertible mixing. According to this fact there is an interesting question: how about the situation of the non-invertible non-linear mixing in BSS or ICA A new simple non-linear mixing model is proposed with a kind of non-invertible mixing, the folding mixing, and method to identify its channel, blindly.