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Independent Component Analysis - an overview ...
jICA is an extension of the popular independent component analysis (ICA). Briefly, ICA is a technique for revealing hidden factors that underlie a set of observable data. ICA has been widely used to solve blind source separation problems (Fig. 16.3); these include, for example, the problem of deriving brain waves recorded using multiple sensors and the problem of removing interfering radio ...
Financial time series forecasting using independent ...
An example is used for illustrating the concept of the TnA method.Fig. 2 shows four financial time series data, each of size 1 × 794, which can be combined as a mixture matrix X of size 4 × 794. After using ICA method to the matrix X, a de-mixing matrix W of size 4 × 4 and four ICs, each of size 1 × 794, can be estimated. The profiles of those four ICs are shown in Fig. 3.
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