A class of neural networks for independent component analysis

Abstract

Independent component analysis (ICA) is a recently developed, useful extension of standard principal component analysis (PCA). The ICA model is utilized mainly in blind separation of unknown source signals from their linear mixtures. In this application only the source signals which correspond to the coefficients of the ICA expansion are of interest. In this paper, we propose neural structures related to multilayer feedforward networks for performing complete ICA. The basic ICA network consists of whitening, separation, and basis vector estimation layers. It can be used for both blind source separation and estimation of the basis vectors of ICA. We consider learning algorithms for each layer, and modify our previous nonlinear PCA type algorithms so that their separation capabilities are greatly improved. The proposed class of networks yields good results in test examples with both artificial and real-world data.

Fast and robust fixed-point algorithms for independent component analysis

“…CONTRAST FUNCTIONS FOR ICA the data [1], [3], [5], [6], [23], [24], [27], [28], [31]: (2) where is an observed -dimensional vector, is andimensional (latent) random vector whose components are assumed mutually independent, and is a constant matrix to be estimated. It is usually further assumed that the dimensions of and are equal, i.e.,…”

Estimation of Output Disturbance in Auto-Regressive Model via Independent Component Analysis

“…The first is our proposed method. The second is Miyaura"s method [7], whose algorithm adopts FastICA [8] and neural networks for ICA [9]; however, the second method is not discussed in detail in this paper owing to space constraints. The sampling time and the signal length for this control system are 0.01 sec and 5.00 sec, respectively.…”

A Pattern Recognition Algorithm for Continuous Tone Images

“…Kumar [6]. PCA can also be applied to 3 independent source images [7] which can be derived through blind source separation procedure like ICA [8], [9]. To solve the problem related to objects belonging to the concept of "cold and warm", "good and bad", etc.…”