نتایج جستجو برای: Independent Component Analysis (ICA transform)
تعداد نتایج: 3635977 فیلتر نتایج به سال:
background: fetal electrocardiography is a developing field that provides valuable information on the fetal health during pregnancy. by early diagnosis and treatment of fetal heart problems, more survival chance is given to the infant. objective: here, we extract fetal ecg from maternal abdominal recordings and detect r-peaks in order to recognize fetal heart rate. on the next step, we find a b...
the brain – computer interface (bci) provides a communicational channel between human and machine. most of these systems are based on brain activities. brain computer-interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. the success of this methodology depends on the selection of methods to process the brain signals in each pha...
Principal Component Analysis (PCA) and Independent Component Analysis (ICA) are the techniques that deal with extracting the independent components from linear mixtures of Gaussian and non-Gaussian data at the input respectively. PCA is a classical method that deals with the second order statistics of data. It is also known as Karhunen-Loeve Transform or the Hotelling Transform in some applicat...
We present a generalization of independent component analysis (ICA), where instead of looking for a linear transform that makes the data components independent, we look for a transform that makes the data components well fit by a tree-structured graphical model. This tree-dependent component analysis (TCA) provides a tractable and flexible approach to weakening the assumption of independence in...
In this paper, a novel Frequency-Domain Independent Component Analysis (ICA-F) approach is proposed to blindly separate and deconvolve the convolutive combinations of digitally modulated signals in wireless communications. This approach relies on the simple observation that if signals are independent in one domain, their corresponding components in a linearly transformed domain are also indepen...
Image fusion is commonly described as the task of enhancing the perception of a scene by combining information captured by different modality sensors. The pyramid decomposition and the Dual-Tree Wavelet Transform have been employed as analysis and synthesis tools for image fusion by the fusion community. Using various fusion rules, one can combine the important features of the input images in t...
The brain – computer interface (BCI) provides a communicational channel between human and machine. Most of these systems are based on brain activities. Brain Computer-Interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. The success of this methodology depends on the selection of methods to process the brain signals in each pha...
The brain – computer interface (BCI) provides a communicational channel between human and machine. Most of these systems are based on brain activities. Brain Computer-Interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. The success of this methodology depends on the selection of methods to process the brain signals in each pha...
The purpose of the ct-image de-noising is an important research topic both in image processing and biomedical engineering. Independent component analysis (ica) is a statistical technique where the goal is to represent a set of random variables as a linear transformation of statistically independent component variables. The curve let transform as a multiscale transform has directional parameters...
We propose an Iterative Nonlinear Gaussianization Algorithm (INGA) which seeks a nonlinear map from a set of dependent random variables to independent Gaussian random variables. A direct motivation of INGA is to extend principal component analysis (PCA), which transforms a set of correlated random variables into uncorrelated (independent up to second order) random variables, and Independent Com...
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