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Complex ICA using nonlinear functions (2008)
| Content Provider | CiteSeerX |
|---|---|
| Author | Adalı, Tülay Li, Hualiang Novey, Mike Cardoso, Jean-François |
| Abstract | Abstract—We introduce a framework based on Wirtinger calculus for nonlinear complex-valued signal processing such that all computations can be directly carried out in the complex domain. The two main approaches for performing independent component analysis, maximum likelihood, and maximization of non-Gaussianity—which are intimately related to each other—are studied using this framework. The main update rules for the two approaches are derived, their properties and density matching strategies are discussed along with numerical examples to highlight their relationships. Index Terms—Complex optimization, density matching, independent component analysis (ICA), maximum-likelihood estimation, negentropy maximization. I. |
| File Format | |
| Journal | IEEE Trans. Signal Process |
| Language | English |
| Publisher Date | 2008-01-01 |
| Access Restriction | Open |
| Subject Keyword | Complex Ica Nonlinear Function Independent Component Analysis Nonlinear Complex-valued Signal Processing Numerical Example Maximum-likelihood Estimation Main Update Rule Density Matching Strategy Complex Domain Main Approach Index Term Complex Optimization Negentropy Maximization Maximum Likelihood Wirtinger Calculus Density Matching |
| Content Type | Text |
| Resource Type | Article |
