ICA Mixture Models for Unsupervised Classification of Non-Gaussian Classes and Automatic Context Switching in Blind Signal Separation

Authors:
Te-Won Lee;Michael S. Lewicki;Terrence J. Sejnowski
Affiliations:
Univ. of California, San Diego, La Jolla;Carnegie Mellon Univ., Pittsburgh, PA;Univ. of California, San Diego, La Jolla
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2000

Citing 12
Cited 40

Blind separation of sources, Part 1: an adaptive algorithm based on neuromimetic architecture

Signal Processing
Independent component analysis, a new concept?

Signal Processing - Special issue on higher order statistics
An information-maximization approach to blind separation and blind deconvolution

Neural Computation
A fast fixed-point algorithm for independent component analysis

Neural Computation
Natural gradient works efficiently in learning

Neural Computation
An alternative perspective on adaptive independent component analysis algorithms

Neural Computation
Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources

Neural Computation
Independent factor analysis

Neural Computation
Unsupervised classification with non-Gaussian mixture models using ICA

Proceedings of the 1998 conference on Advances in neural information processing systems II
Learning Overcomplete Representations

Neural Computation
Blind separation of mixture of independent sources through aquasi-maximum likelihood approach

IEEE Transactions on Signal Processing
Blind source separation-semiparametric statistical approach

IEEE Transactions on Signal Processing

An Algebraic Formalism for Computing the Moments of Distributions of Quadratic Forms

Automation and Remote Control
Separation of independent components from data mixed by several mixing matrices

Signal Processing - Signal processing with heavy-tailed models
Variational mixture of Bayesian independent component analyzers

Neural Computation
Improving Naive Bayes Using Class-Conditional ICA

IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Breast Tissue Classification in Mammograms Using ICA Mixture Models

ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Feature Subset Selection in an ICA Space

CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
Variational learning of clusters of undercomplete nonsymmetric independent components

The Journal of Machine Learning Research
Unified probabilistic models for face recognition from a single example image per person

Journal of Computer Science and Technology
Feature Extraction Using Independent Components of Each Category

Neural Processing Letters
A Bayesian method for identifying independent sources of non-random spatial patterns

Statistics and Computing
Exploring Latent Structure of Mixture ICA Models by the Minimum β-Divergence Method

Neural Computation
A Hierarchical Bayesian Model for Learning Nonlinear Statistical Regularities in Nonstationary Natural Signals

Neural Computation
A Variational Method for Learning Sparse and Overcomplete Representations

Neural Computation
A Parallel Independent Component Analysis Algorithm

ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
EMPATH: A Neural Network that Categorizes Facial Expressions

Journal of Cognitive Neuroscience
Independent component analysis in signals with multiplicative noise using fourth-order statistics

Signal Processing
Capturing nonlinear dependencies in natural images using ICA and mixture of Laplacian distribution

Neurocomputing
A reconfigurable FPGA system for parallel independent component analysis

EURASIP Journal on Embedded Systems
A gradient-based optimum block adaptation ICA technique for interference suppression in highly dynamic communication channels

EURASIP Journal on Applied Signal Processing
Improvements on ICA mixture models for image pre-processing and segmentation

Neurocomputing
ICA mixture model algorithm for unsupervised classification of remote sensing imagery

International Journal of Remote Sensing
A survey of image classification methods and techniques for improving classification performance

International Journal of Remote Sensing
Discovery of Linear Non-Gaussian Acyclic Models in the Presence of Latent Classes

Neural Information Processing
ICA Mixture Modeling for the Classification of Materials in Impact-Echo Testing

ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
A general procedure for learning mixtures of independent component analyzers

Pattern Recognition
Ice hockey shot event modeling with mixture hidden Markov model

EiMM '09 Proceedings of the 1st ACM international workshop on Events in multimedia
Fast communication: On including sequential dependence in ICA mixture models

Signal Processing
Image similarity based on hierarchies of ICA mixtures

ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
An EM algorithm for independent component analysis using an AR-GGD source model

AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Portuguese pronoun resolution: resources and evaluation

CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
A non-parametric approach for independent component analysis using kernel density estimation

CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
ICA mixtures applied to ultrasonic nondestructive classification of archaeological ceramics

EURASIP Journal on Advances in Signal Processing - Special issue on signal processing in advanced nondestructive materials inspection
ICA with time-varying convergence factor and its application in communications

ICCOM'06 Proceedings of the 10th WSEAS international conference on Communications
Nonlinear prediction based on independent component analysis mixture modelling

IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Super-Gaussian mixture source model for ICA

ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Learning overcomplete representations with a generalized gaussian prior

TAMC'06 Proceedings of the Third international conference on Theory and Applications of Models of Computation
Ice hockey shooting event modeling with mixture hidden Markov model

Multimedia Tools and Applications
Unsupervised classification of audio signals by self-organizing maps and bayesian labeling

HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Measuring non-gaussianity by phi-transformed and fuzzy histograms

Advances in Artificial Neural Systems - Special issue on Advances in Unsupervised Learning Techniques Applied to Biosciences and Medicine
Target detection based on a dynamic subspace

Pattern Recognition

Quantified Score

Hi-index	0.14

Visualization

Abstract

An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of independent, non-Gaussian densities. The algorithm estimates the density of each class and is able to model class distributions with non-Gaussian structure. The new algorithm can improve classification accuracy compared with standard Gaussian mixture models. When applied to blind source separation in nonstationary environments, the method can switch automatically between classes, which correspond to contexts with different mixing properties. The algorithm can learn efficient codes for images containing both natural scenes and text. This method shows promise for modeling non-Gaussian structure in high-dimensional data and has many potential applications.