A Fast Fixed-Point Algorithm for Independent Component Analysis of Complex Valued Signals

By Ella Bingham, Aapo Hyvärinen. International Journal of Neural Systems, 2000

2,142 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Artificial Intelligence, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b5de7a45843a538fecff93c3e1fa7d1e8c06511f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. T. Adalı
2. Johan Himberg
3. Louis L. Scharf
4. Peter J. Schreier
5. Te-Won Lee
6. Seyed Hossein Hosseinian
7. Andreas Mayr
8. F. Karimzadeh

In Artificial Intelligence

1. Sepp Hochreiter
2. T. Adalı
3. Te-Won Lee
4. Johan Himberg
5. Martin Heusel
6. Louis L. Scharf
7. Peter J. Schreier
8. Andreas Mayr

In Signal Processing

1. Johan Himberg
2. T. Adalı
3. Aapo Hyvärinen
4. Te-Won Lee
5. Louis L. Scharf
6. Peter J. Schreier
7. Seyed Hossein Hosseinian
8. Andreas Mayr

Citations in the corpus

• A Novel Method for Noninvasive Estimation of Utility Harmonic Impedance Based on Complex Independent Component Analysis (2015, methodology): “The complete description of the complex FastICA algorithm is available in [12].”
• Unsupervised image classification, segmentation, and enhancement using ICA mixture models (2002, methodology): “There are several methods for adapting the basis functions in the ICA model [4], [11], [14], [21], [26].”
• Independent component analysis for financial time series (2000, methodology): “Using a suitable normalizing term, we arrive at the following iteration [ 13 ]: 1. We a random initial vector w(0) of norm 1. Let”
• Recognizing human motion with multiple acceleration sensors (2001, methodology): “In this study, the FastICA algorithm has been used [ 6 ], [7].”
• Complex-Valued Signal Processing: The Proper Way to Deal With Impropriety (2011, background): “These are conditions for the cost function to have a local minimum or maximum [88], following the approach in [18], which assumed circularity.”
• Efficient independent component analysis (2006, methodology): “The ICA algorithms used for comparison in Section 4 such as FastICA [Hyvarinen and Oja (1997)] and extended infomax [19] are of this type.”
• FABIA: factor analysis for bicluster acquisition (2010, methodology): “Sparseness is obtained by a component-wise independent Laplace distribution (Hyvärinen and Oja, 1999), which is now used as a prior on the factors z̃ instead of the Gaussian:”
• All-sky astrophysical component separation with Fast Independent Component Analysis (FastICA) (2001, methodology): “In this section, we summarize an efficient strategy, described in detail in Hyvärinen & Oja (1997) and Hyvärinen (1999), to separate the independent components s, exploiting these assumptions.”