Journal ArticleDOI
ICA with Reference
TLDR
A neural algorithm is proposed using a Newton-like approach to obtain an optimal solution to the constrained optimization problem and experiments with synthetic signals and real fMRI data demonstrate the efficacy and accuracy of the proposed algorithm.About:
This article is published in Neurocomputing.The article was published on 2006-10-01. It has received 216 citations till now. The article focuses on the topics: Independent component analysis & Constrained optimization.read more
Citations
More filters
Journal ArticleDOI
EEG artifact removal?state-of-the-art and guidelines
TL;DR: This paper presents an extensive review on the artifact removal algorithms used to remove the main sources of interference encountered in the electroencephalogram (EEG), specifically ocular, muscular and cardiac artifacts, and concludes that the safest approach is to correct the measured EEG using independent component analysis-to be precise, an algorithm based on second-order statistics such as second- order blind identification (SOBI).
Journal ArticleDOI
Independent component analysis for biomedical signals.
Christopher J. James,C.W. Hesse +1 more
TL;DR: The basic assumptions that are made when applying ICA are discussed, along with their implications when applied particularly to biomedical signals, and the criterion used for establishing independence between sources is reviewed and this leads to the introduction of ICA/BSS techniques based on time, frequency and joint time-frequency decomposition of the data.
Journal ArticleDOI
Unmixing fMRI with independent component analysis
Vince D. Calhoun,Tulay Adali +1 more
TL;DR: ICA has recently demonstrated considerable promise in characterizing functional magnetic resonance imaging data, primarily due to its intuitive nature and ability for flexible characterization of the brain function.
Journal ArticleDOI
A New Constrained Independent Component Analysis Method
De-Shuang Huang,Jian-Xun Mi +1 more
TL;DR: A new improved algorithm for cICA is presented through the investigation of the inequality constraints, in which different closeness measurements are compared.
Journal ArticleDOI
Dual Deep Network for Visual Tracking
TL;DR: The proposed dual network is updated online in a unique manner based on the observation, that the target being tracked in consecutive frames should share more similar feature representations than those in the surrounding background.
References
More filters
Book
Probability, random variables and stochastic processes
TL;DR: This chapter discusses the concept of a Random Variable, the meaning of Probability, and the axioms of probability in terms of Markov Chains and Queueing Theory.
Book
Probability, random variables, and stochastic processes
TL;DR: In this paper, the meaning of probability and random variables are discussed, as well as the axioms of probability, and the concept of a random variable and repeated trials are discussed.
Journal ArticleDOI
An information-maximization approach to blind separation and blind deconvolution
TL;DR: It is suggested that information maximization provides a unifying framework for problems in "blind" signal processing and dependencies of information transfer on time delays are derived.
Journal ArticleDOI
Independent component analysis, a new concept?
TL;DR: An efficient algorithm is proposed, which allows the computation of the ICA of a data matrix within a polynomial time and may actually be seen as an extension of the principal component analysis (PCA).
Journal ArticleDOI
Fast and robust fixed-point algorithms for independent component analysis
TL;DR: Using maximum entropy approximations of differential entropy, a family of new contrast (objective) functions for ICA enable both the estimation of the whole decomposition by minimizing mutual information, and estimation of individual independent components as projection pursuit directions.