This article needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. Find sources: "Independent component analysis" – news · newspapers · books · scholar · JSTOR(October 2011) (Learn how and when to remove this message)
Part of a series on
Machine learning and data mining
Paradigms
Supervised learning
Unsupervised learning
Online learning
Batch learning
Meta-learning
Semi-supervised learning
Self-supervised learning
Reinforcement learning
Curriculum learning
Rule-based learning
Quantum machine learning
Problems
Classification
Generative modeling
Regression
Clustering
Dimensionality reduction
Density estimation
Anomaly detection
Data cleaning
AutoML
Association rules
Semantic analysis
Structured prediction
Feature engineering
Feature learning
Learning to rank
Grammar induction
Ontology learning
Multimodal learning
Supervised learning (classification • regression)
Apprenticeship learning
Decision trees
Ensembles
Bagging
Boosting
Random forest
k-NN
Linear regression
Naive Bayes
Artificial neural networks
Logistic regression
Perceptron
Relevance vector machine (RVM)
Support vector machine (SVM)
Clustering
BIRCH
CURE
Hierarchical
k-means
Fuzzy
Expectation–maximization (EM)
DBSCAN
OPTICS
Mean shift
Dimensionality reduction
Factor analysis
CCA
ICA
LDA
NMF
PCA
PGD
t-SNE
SDL
Structured prediction
Graphical models
Bayes net
Conditional random field
Hidden Markov
Anomaly detection
RANSAC
k-NN
Local outlier factor
Isolation forest
Artificial neural network
Autoencoder
Cognitive computing
Deep learning
DeepDream
Feedforward neural network
Kolmogorov–Arnold Network
Recurrent neural network
LSTM
GRU
ESN
reservoir computing
Restricted Boltzmann machine
GAN
Diffusion model
SOM
Convolutional neural network
U-Net
Transformer
Vision
Mamba
Spiking neural network
Memtransistor
Electrochemical RAM (ECRAM)
Reinforcement learning
Q-learning
SARSA
Temporal difference (TD)
Multi-agent
Self-play
Learning with humans
Active learning
Crowdsourcing
Human-in-the-loop
RLHF
Model diagnostics
Coefficient of determination
Confusion matrix
Learning curve
ROC curve
Mathematical foundations
Kernel machines
Bias–variance tradeoff
Computational learning theory
Empirical risk minimization
Occam learning
PAC learning
Statistical learning
VC theory
Machine-learning venues
ECML PKDD
NeurIPS
ICML
ICLR
IJCAI
ML
JMLR
Related articles
Glossary of artificial intelligence
List of datasets for machine-learning research
List of datasets in computer vision and image processing
Outline of machine learning
v
t
e
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that at most one subcomponent is Gaussian and that the subcomponents are statistically independent from each other.[1] ICA was invented by Jeanny Hérault and Christian Jutten in 1985.[2] ICA is a special case of blind source separation. A common example application of ICA is the "cocktail party problem" of listening in on one person's speech in a noisy room.[3]
^"Independent Component Analysis: A Demo".
^Cite error: The named reference jutten85 was invoked but never defined (see the help page).
In signal processing, independentcomponentanalysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents....
Principal componentanalysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...
principal components analysisComponentanalysis (statistics), any analysis of two or more independent variables Connected-componentanalysis, in graph theory...
principal componentanalysis (PCA), independentcomponentanalysis (ICA), linear discriminant analysis (LDA) and canonical correlation analysis (CCA). Multilinear...
points in the dataset. Examples include dictionary learning, independentcomponentanalysis, matrix factorization and various forms of clustering. In self-supervised...
methods of analysis focus either on independentcomponents or on regions of correlation.[citation needed] Independentcomponentanalysis (ICA) is a useful...
element analysis – a computer simulation technique used in engineering analysisIndependentcomponentanalysis Link quality analysis – the analysis of signal...
Information Science Ruye Wang, IndependentComponentAnalysis, node4: Measures of Non-Gaussianity P. Comon, IndependentComponentAnalysis – a new concept?, Signal...
Dependent componentanalysis (DCA) is a blind signal separation (BSS) method and an extension of Independentcomponentanalysis (ICA). ICA is the separating...
etc. Independentcomponentanalysis (ICA) is another signal processing solution that separates different signals that are statistically independent in time...
of the more successful approaches are principal componentsanalysis and independentcomponentanalysis, which work well when there are no delays or echoes...
FastICA is an efficient and popular algorithm for independentcomponentanalysis invented by Aapo Hyvärinen at Helsinki University of Technology. Like...
considered at a particular level of analysis Lumped element model, a model of spatially distributed systems Component video, a type of analog video information...
detectable through independentcomponentanalysis of resting state fMRI images, as well as seed based functional connectivity analysis. The functional connectivity...
multivariate statistics, kernel principal componentanalysis (kernel PCA) is an extension of principal componentanalysis (PCA) using techniques of kernel methods...
the basic processing tools, EEGLAB implements independentcomponentanalysis (ICA), time/frequency analysis, artifact rejection, and several modes of data...
robust effect of finding the DMN with resting-state scans and independentcomponentanalysis (ICA). Another reason was that the DMN could be measured with...
Functional principal componentanalysis (FPCA) is a statistical method for investigating the dominant modes of variation of functional data. Using this...
distribution Independence of irrelevant alternatives IndependentcomponentanalysisIndependent and identically distributed random variables Index (economics)...
His postdoc, Tony Bell, developed the infomax algorithm for IndependentComponentAnalysis (ICA) which has been widely adopted in machine learning, signal...
the applications of infomax has been to an independentcomponentanalysis algorithm that finds independent signals by maximizing entropy. Infomax-based...
Hierarchical ensembles based on Gabor Fisher classifier and independentcomponentanalysis preprocessing techniques are some of the earliest ensembles...
Global Information