—Modeling natural and artificial systems has played a key role in various applications and has long been a task that has drawn enormous efforts. In this work, instead of explori...
Ronen Talmon, Dan Kushnir, Ronald R. Coifman, Isra...
Independent component analysis (ICA) is possibly the most widespread approach to solve the blind source separation (BSS) problem. Many different algorithms have been proposed, tog...
Jarkko Ylipaavalniemi, Nima Reyhani, Ricardo Vig&a...
Studying image intensity change in each pixel in dynamic contrast enhanced (DCE)-MRI data enables differentiation of different tissue types based on their difference in contrast u...
Hatef Mehrabian, Ian Pang, Chaitanya Chandrana, Ra...
In this paper, we present a new independent component analysis mixture vector quantization (ICAMVQ) method to summarize the video content. In particular, independent component ana...
In the independent component analysis, polynomial functions of higher order statistics are often used as cost functions. However, such cost functions usually have many local minim...
The aim of this paper is to provide an algorithm for image fusion which combines the techniques of Chebyshev polynomial (CP) approximation and independent component analysis (ICA)...
Accurately evaluating statistical independence among random variables is a key element of Independent Component Analysis (ICA). In this paper, we employ a squared-loss variant of ...
Abstract. Independent Subspace Analysis (ISA) is an extension of Independent Component Analysis (ICA) that aims to linearly transform a random vector such as to render groups of it...
The posterior parietal cortex (PPC) plays an important role in motor planning and execution. Here, we investigated whether noninvasive electroencephalographic (EEG) signals recorde...
Abstract. We propose a brain-computer interface (BCI) system for evolving images in realtime based on subject feedback derived from electroencephalography (EEG). The goal of this s...