Results 251 to 260 of about 27,220,972 (292)

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
openaire   +2 more sources

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
openaire   +1 more source

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.
Chiu Shun Wong, Dragan Obradovic, Nilesh Madhu   +2 more
openaire   +2 more sources

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.
Kannammal Annadurai, S. Subha Rani
openaire   +2 more sources

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
openaire   +1 more source

Visualisasi Kerusakan Bearing Menggunakan Metode Independent Component Analysis (ICA)

Bandung Conference Series: Statistics, 2022
Abstract. Vibration is a response of a mechanical system either caused by a given excitation force or changes in operating conditions as a function of time. The force that causes this vibration can be caused by several sources such as contact/impact between moving/rotating components, rotation of an unbalanced mass, misalignment and also Bearing faults
Silvya Rahmatiara Putri, Sutawanir Darwis   +1 more
openaire   +1 more source

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
openaire   +1 more source

An empirical method to select dominant independent components in ICA for time series analysis

IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 2003
Back and Weigend (1997) showed that the dominant independent components obtained by independent component analysis (ICA) can reveal more underlying structure of the time series than principal component analysis. To find those dominant independent components, all the independent components are listed in an appropriate order and then a subset of ...
Yiu-Ming Cheung, Lei Xu 0001
openaire   +2 more sources

Blind calibration of five-port receiver based on Independent Component Analysis (ICA)

2013 Wireless Telecommunications Symposium (WTS), 2013
Five-port direct conversion receiver has been demonstrated as an interesting alternative for application in software-defined radio since its design is simple and it can operate in a wide range of frequencies. However, in order to carry out in-phase and quadrature demodulation, the five-port receiver must be calibrated for each frequency and modulation ...
Francisco Vidal, Adrião Duarte Dória Neto, Allan de Medeiros Martins, Bernard Huyart   +3 more
openaire   +1 more source

A Grid Application for an Evaluation of Brain Function using Independent Component Analysis (ICA)

2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'02), 2003
For the effective and early diagnosis of brain diseases, we have developed an evaluation system for brain function using an Independent Component Analysis (ICA) method. This evaluation system benefits greatly from the newly emerged Grid. To embody a Grid environment, a Globus grid toolkit has been utilized as a building block.
Yuko Mizuno-Matsumoto, Susumu Date, Takeshi Kaishima, Youki Kadobayashi, Shinji Shimojo   +4 more
openaire   +2 more sources