Results 241 to 250 of about 150,011 (287)

Separation of deterministic signals using independent component analysis (ICA)

Studia Geophysica et Geodaetica, 2012
Independent Component Analysis (ICA) represents a higher-order statistical technique that is often used to separate mixtures of stochastic random signals into statistically independent sources. Its benefit is that it only relies on the information contained in the observations, i.e.
Ehsan Forootan, Jürgen Kusche
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Homeopathic ICA: A simple approach to expand the use of independent component analysis (ICA)

Chemometrics and Intelligent Laboratory Systems, 2015
Abstract Independent component analysis (ICA) is an increasingly popular method to resolve complex data sets, such as chemical image data, into images and their associated spectra. Unfortunately, the pre-requisite of statistical independence severely limits the application of ICA.
W. Windig, M.R. Keenan
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Independent Component Analysis (ICA) Using Pearsonian Density Function

2009
Independent component analysis (ICA) is an important topic of signal processing and neural network which transforms an observed multidimensional random vector into components that are mutually as independent as possible. In this paper, we have introduced a new method called SwiPe-ICA ( S tep wi se Pe arsonian ICA) that combines the methodology of ...
Abhijit Mandal, Arnab Chakraborty
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Robust techniques for independent component analysis (ICA) with noisy data

Neurocomputing, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cichocki, A., Douglas, S. C., Amari, S.
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Face Recognition using independent component analysis of GaborJet (GaborJet-ICA)

2010 6th International Colloquium on Signal Processing & its Applications, 2010
In this paper a new face recognition technique based on Independent Component Analysis of GaborJet (GaborJet-ICA) is proposed. Existing face recognition systems using Gabor wavelets convolve a whole face image with a set of 40 Gabor wavelets. We have derived Gabor feature vector from facial landmarks (fiducial points) known as GaborJets.
K S Kinage, S G Bhirud
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A Robust Adaptive Filtering Method based on Independent Component Analysis (ICA)

2020 13th International Conference on Communications (COMM), 2020
The purpose of this paper is to present a method that uses Independent Component Analysis (ICA) in order to filter real-valued signals. The method is highly robust to noise, as it can estimate with high precision the noise that affects the input signal. To underline this, comparisons to high order, multiband FIR filters are performed.
Leontin Tuta, Mircea Nicolaescu, Georgiana Rosu, Alexandru Grivei, Bogdan Barbulescu   +4 more
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Authentication of DICOM medical images using independent component analysis (ICA)

International Journal of Medical Engineering and Informatics, 2012
This paper proposes a blind content-based watermarking scheme for image authentication using ICA and DCT. The watermark to be embedded is obtained from the host image itself in terms of the Frobenius norm of the mixing matrix obtained during ICA. These are embedded in the mid-frequency DCT coefficients.
A. Kannammal, S. Subha Rani
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Process Monitoring Based on Independent Component Analysis−Principal Component Analysis (ICA−PCA) and Similarity Factors

Industrial & Engineering Chemistry Research, 2007
Many of the current multivariate statistical process monitoring techniques (such as principal component analysis (PCA) or partial least squares (PLS)) do not utilize the non-Gaussian information of...
Zhiqiang Ge, Zhihuan Song
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An Independent Component Analysis (ICA) Based Approach for EEG Person Authentication

2009 3rd International Conference on Bioinformatics and Biomedical Engineering, 2009
Exploring brain electrical activity represented by electroencephalogram (EEG) signals for biometric applications has recently attracted increasing research attention since EEG pattern has been shown to be unique for each individual. In this paper, we propose an Independent Component Analysis (ICA) based EEG feature extraction and modeling approach for ...
Chen He, Jane Wang
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Independent component analysis (ICA) for blind equalization of frequency selective channels

2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718), 2004
In this paper we address the problem of blind source separation (BSS) in frequency selective multiple-input multiple-output (MIMO) channels, when the only available prior knowledge about the transmitted signals is their mutual statistical independence. The novelty of the paper is two-fold.
null Chiu Shun Wong, D. Obradovic, N. Madhu   +2 more
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