Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

In this paper, we review recent advances in blind source separation (BSS) and independent
component analysis (ICA) for nonlinear mixing models. After a general introduction to BSS …

For many years, artificial neural networks (ANNs) have been studied and used to model
information processing systems based on or inspired by biological neural structures. They …

Forecasting stock prices is a major activity of financial firms and private investors. In
developing a stock price forecasting model, the first step is usually feature extraction …

With the economic successes of several Asian economies and their increasingly important
roles in the global financial market, the prediction of Asian stock markets has becoming a hot …

Both signal processing and image processing are playing increasingly important roles in
remote sensing. As most data from satellites are in image form, image processing has been …

This paper proposes a repeated blind source separation (BSS) method based on
morphological filtering and singular value decomposition (SVD) to separate the mixed …

This paper aims to overcome two major defects with the traditional rock image classification
framework based on convolutional neural network (CNN), namely, slow training and poor …

One of the major activities of financial firms and private investors is to predict future prices of
stocks. However, stock index prediction is regarded as a challenging task of the prediction …

In this paper, we propose nonlinear tensor analysis methods: the tensor self-organizing map
(TSOM) and the tensor generative topographic mapping (TGTM). TSOM is a straightforward …