Blind Recognition of TT&C Signals of Satellite Based on JTFA and Fast-ICA Algorithm

2021 ◽  
pp. 215-221
Author(s):  
Wang Le ◽  
MingXiang Guang ◽  
JingDan Zhang
Keyword(s):  
Ica Algorithm ◽  
Blind Recognition

Blind Recognition Algorithm of TT&C Signals of Satellite Based on Fast-ICA Algorithm

2013 ◽  
Vol 462-463 ◽  
pp. 237-242
Author(s):  
Le Wang ◽  
Jing Dan Zhang
Keyword(s):  
Objective Function ◽  
Basic Principle ◽  
Recognition Algorithm ◽  
New Method ◽  
Good Convergence ◽  
Simulation Results ◽  
Ica Algorithm ◽  
Blind Recognition

A blind sub-carrier recognition algorithm of TT&C communication is proposed based on Negentropy-maximization in terms of recognition of TT&C signals for military TT&C communication information scout. First, the basic principle of the ICA is discussed in this paper. Using maximum Negentropy approximation of differential Negentropy, an objective function for ICA is introduced and a Fast-ICA algorithm based on maximum Negentropy is presented. Based on analyzing Fast-ICA algorithm deeply, this paper expounds a new method to adopt it in the recognition of TT&C signals of satellite. Simulation results in MATLAB show its better performance and efficiency in the mixed TT&C signals of satellite recognition, proving its good convergence and robust.

An Optimal ICA Algorithm Applied to fMRI DATA

2007 ◽  
Author(s):  
Xian-Chuan Yu ◽  
Jia-Mian Ren ◽  
Nan Zhang ◽  
Guo-Sheng Ding
Keyword(s):  
Fmri Data ◽  
Ica Algorithm

A Novel Blind Watermark Extraction Algorithm Based on Nonsubsampled Contourlet Transform

2014 ◽  
Vol 989-994 ◽  
pp. 1901-1904
Author(s):  
Lei Feng ◽  
Xiao Fei Shi ◽  
Hong Yu Chen ◽  
Yan Hua Li ◽  
Yue Long Zhang
Keyword(s):  
Prior Knowledge ◽  
Blind Source Separation ◽  
Extraction Method ◽  
Low Frequency ◽  
Contourlet Transform ◽  
Nonsubsampled Contourlet Transform ◽  
Independent Components ◽  
Extraction Algorithm ◽  
Blind Extraction ◽  
Ica Algorithm

Most existing watermark extraction algorithms were dependent on prior knowledge. This paper proposed a blind extraction method without relying on prior knowledge. According to constructing new observation based on nonsubsampled contourlet transform, which utilizes low frequency and directional components of watermarked image, more independent components are generated. We involve these components into watermarked image and resort this solution to multichannel blind source separation. Estimated watermark is recovered by ICA algorithm. Experiment results indicate that the proposed method can achieve better results in contrast with two existing algorithms.

scholarly journals gpICA: A Novel Nonlinear ICA Algorithm Using Geometric Linearization

2006 ◽  
Vol 2007 (1) ◽  
Author(s):  
Thang Viet Nguyen ◽  
Jagdish Chandra Patra ◽  
Sabu Emmanuel
Keyword(s):  
Ica Algorithm ◽  
Geometric Linearization

Regression ICA Algorithm for Image Denoising

2008 ◽  
pp. 993-997 ◽  
Author(s):  
Shangming Yang ◽  
Zhang Yi ◽  
Guisong Liu
Keyword(s):  
Image Denoising ◽  
Ica Algorithm

scholarly journals Real Time Blind Source Separation in Reverberant Environments

2021 ◽  
Author(s):  
◽  
Timothy Sherry
Keyword(s):  
Real Time ◽  
Blind Source Separation ◽  
Real World ◽  
Source Separation ◽  
Real World Data ◽  
The Core ◽  
Reverberant Environments ◽  
Ica Algorithm ◽  
Stationary Sources ◽  
Convolutive Blind Source Separation

<p>An online convolutive blind source separation solution has been developed for use in reverberant environments with stationary sources. Results are presented for simulation and real world data. The system achieves a separation SINR of 16.8 dB when operating on a two source mixture, with a total acoustic delay was 270 ms. This is on par with, and in many respects outperforms various published algorithms [1],[2]. A number of instantaneous blind source separation algorithms have been developed, including a block wise and recursive ICA algorithm, and a clustering based algorithm, able to obtain up to 110 dB SIR performance. The system has been realised in both Matlab and C, and is modular, allowing for easy update of the ICA algorithm that is the core of the unmixing process.</p>

An Extended Online Fast-ICA Algorithm

2006 ◽  
pp. 1109-1114 ◽  
Author(s):  
Gang Wang ◽  
Ni-ni Rao ◽  
Zhi-lin Zhang ◽  
Quanyi Mo ◽  
Pu Wang
Keyword(s):  
Ica Algorithm
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