Aapo Hyvärinen

Independent Component Analysis

Independent component analysis of nondeterministic fMRI signal sources

Independent component analysis: algorithms and applications

Fast and robust fixed-point algorithms for independent component analysis

Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent fr...

A Fast Fixed-Point Algorithm for Independent Component Analysis

We introduce a novel fast algorithm for independent component analysis, which can be used for blind source separation and feature extraction. We show how a neural network learni...

SURVEY OF INDEPENDENT COMPONENT ANALYSIS

A common problem encountered in such disciplines as statistics, data analysis, signal processing, and neural network research, is nding a suitable representation of multivariate...

Sparse Code Shrinkage: Denoising of Nongaussian Data by Maximum Likelihood Estimation

Sparse coding is a method for finding a representation of data in which each of the components of the representation is only rarely significantly active. Such a representation i...

Independent component analysis by general nonlinear Hebbian-like learning rules

Gaussian moments for noisy independent component analysis

A novel approach for the problem of estimating the data model of independent component analysis (or blind source separation) in the presence of Gaussian noise is introduced. We ...

The Fixed-Point Algorithm and Maximum Likelihood Estimation for Independent Component Analysis

Independent component analysis in the presence of Gaussian noise by maximizing joint likelihood

Independent Component Analysis

In this chapter, we discuss a statistical generative model called independent component analysis. It is basically a proper probabilistic formulation of the ideas underpinning sp...