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A Fast Convergence Adaptive Complex-Valued Blind Source Separation Method
2017
Journal of Information Hiding and Multimedia Signal Processing
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This paper deals with adaptive blind source separation of noncircular signals from a complex-valued mixing signal. ...
By incorporating the restriction that the separating matrix of white mixing signals should be a unitary matrix in the gradient cost function, an adaptive complex-valued blind source separation method with ...
Complex-valued blind source separation is used to separate an original signal from a complex-valued mixing signal. ...
dblp:journals/jihmsp/Jia017
fatcat:ujqphfvmg5eybdwv5qwxlmoyii
Research and Application of Noise Blind Mixed Signal On-line Separation Algorithm Based on ICA
2014
Open Cybernetics and Systemics Journal
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In the application of gradient algorithm, in order to solve the compromise between convergence rate and stability performance of the natural gradient blind source separation algorithm, the variable step ...
size natural gradient algorithm was adopted to complete the noise electrical signal on-line blind source separation simulation, which provides an effective method to realize the multi-sensor collection ...
When using natural gradient method to realize the blind source separation, it is very important to choose a step size. ...
doi:10.2174/1874110x01408010479
fatcat:sbbgpswagjf4fep7572k6zbdqq
Adaptive Complex-Valued Independent Component Analysis Based on Second-Order Statistics
2016
Journal of Electrical and Computer Engineering
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This paper proposes a two-stage fast convergence adaptive complex-valued independent component analysis based on second-order statistics of complex-valued source signals. ...
Compared with other adaptive complex-valued independent component analysis, the proposed method shows a faster convergence rate and smaller error. ...
This changes the updating direction of the separating matrix and leads to slow convergence speed. To increase the rate of convergence, a fast complex-valued ICA method is proposed in this work. ...
doi:10.1155/2016/2467198
fatcat:tibwpkueurfwlgw5iuzohfholu
A Novel Floating Point Fast Confluence Adaptive Independent Component Analysis for Signal Processing Applications
2013
Advances in Signal Processing
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The high convergence speed is achieved by a novel optimization scheme that adaptively changes the weight vector based on the kurtosis value. ...
This paper presents a floating point implementation of a novel fast confluence adaptive independent component analysis (FCAICA) technique with reduced number of iterations that provides the high convergence ...
A frequency-domain method of blind source separation (FD-BSS) is able to separate acoustic sources under highly reverberant challenging conditions [11] . ...
doi:10.13189/asp.2013.010301
fatcat:bvcsxtadfrfzbh6y5pim47epum
Adaptive blind source separation for virtually any source probability density function
2000
IEEE Transactions on Signal Processing
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Index Terms-Adaptive algorithms, blind source separation, closed-form estimation, convergence and performance analysis, higher order statistics. ...
Blind source separation (BSS) aims to recover a set of statistically independent source signals from a set of linear mixtures of the same sources. ...
ADAPTIVE SOURCE SEPARATION
A. ...
doi:10.1109/78.823974
fatcat:5svivoahvzedzmhxaetskfwzc4
A Survey of Optimization Methods for Independent Vector Analysis in Audio Source Separation
2023
Sensors
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For multichannel speech signals, independent component analysis (ICA) requires a certain statistical independence of source signals and other conditions to allow blind separation. independent vector analysis ...
It has become extremely important to extract useful signals by decomposing various mixed signals through blind source separation (BSS). ...
[29] proposed a blind separation algorithm for IVA based on step-size adaptation. ...
doi:10.3390/s23010493
pmid:36617090
pmcid:PMC9824503
fatcat:ymlbi4mt4bfwrozv3zmhurgwti
Natural gradient multichannel blind deconvolution and speech separation using causal FIR filters
2005
IEEE Transactions on Speech and Audio Processing
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Natural gradient adaptation is an especially convenient method for adapting the coefficients of a linear system in inverse filtering tasks such as convolutive blind source separation and multichannel blind ...
Numerical experiments verify the robust convergence performance of the new method both in multichannel blind deconvolution tasks for i.i.d. sources and in convolutive BSS tasks for real-world acoustic ...
Fast Implementation In some multichannel blind deconvolution or convolutive BSS tasks, a larger separation filter length value may be required for adequate performance. ...
doi:10.1109/tsa.2004.838538
fatcat:w6xpxjwuv5dtjayxfhnsaswi4u
A Fast Adaptive Speech Extraction Method using Blind Source Separation for Audio Signal Processing
2020
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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The methods vary on time, frequency and statistical approach. In this paper, the source speech signals are separated using different methods like FastICA,PCA and kICA. ...
The adaptive signal processing methods are used in several applications like channel estimation, Noise removal and extraction of signals also. ...
Thus the BSS algorithm will modify the speech source that is simulated as spatial audio. Y. Zhang and S. A. Kassam (2010) discuss complex blind source separation. ...
doi:10.35940/ijitee.b7253.029420
fatcat:hpxmwtetundsjpun2vxa2tg2ky
Promoting convergence in multi-channel blind signal separation using PNLMS
2011
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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The PNLMS based blind speech separation is suitable for real-time implementation as it promises faster convergence and requires only a modest increase in complexity as compared to the NLMS algorithm. ...
In this paper, we investigate the use of PNLMS algorithm for blind speech separation and show that with a careful selection of operating parameters the PNLMS algorithm greatly helps promote convergence ...
With a modest increase in complexity, the new method outperforms the conventional NLMS-based method in terms of the time taken to converge to the true solution. ...
doi:10.1109/icassp.2011.5946838
dblp:conf/icassp/Ikram11
fatcat:xc5y2pwt5nbmtcnrigtwlaqcvi
Adaptive separation of acoustic sources for anechoic conditions: A constrained frequency domain approach
2003
Speech Communication
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Starting from a general blind source separation algorithm for Fourier transformed speech signals, the free field assumption is incorporated into the framework, yielding a simple, fast and adaptive algorithm ...
Blind source represents a signal processing technique with a large potential for noise reduction. ...
The helpful comments of three anonymous reviewers on a former draft of the manuscript are gratefully acknowledged. ...
doi:10.1016/s0167-6393(02)00060-2
fatcat:z6n6i5zdrvfmnlg2xdd34r5tty
Variable Step-Size Method Based on a Reference Separation System for Source Separation
2015
Journal of Sensors
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This paper proposes a novel variable step-size method based on reference separation system for online blind source separation. ...
Traditional variable step-size methods are effective to solve the problem of choosing step-size in adaptive blind source separation process. ...
Conclusion In this paper, we propose a new variable step-size algorithm for blind source separation. ...
doi:10.1155/2015/964098
fatcat:idwtqvlp2balbi45aevptqmesm
Analysis of Blind Separation of Noisy Mixed Images Based on Wavelet Thresholding and Independent Component Analysis
2011
International Journal of Engineering and Technology
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Index Terms-Blind source separation (BSS), fast ICA, Independent component analysis (ICA), Wavelet threshold. ...
The second approach uses wavelet threshold to de-noise and then use the fast ICA algorithm to separate the de-noised images. ...
Examples include equivariant adaptive source separation [8] , fast ICA [9] , and efficient Fast ICA [10] . ...
doi:10.7763/ijet.2011.v3.285
fatcat:hfq3hjxsmbhbrgbho3srevp62m
Sampling Adaptive Learning Algorithm for Mobile Blind Source Separation
2018
Wireless Communications and Mobile Computing
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Learning rate plays an important role in separating a set of mixed signals through the training of an unmixing matrix, to recover an approximation of the source signals in blind source separation (BSS) ...
To improve the algorithm in speed and exactness, a sampling adaptive learning algorithm is proposed to calculate the adaptive learning rate in a sampling way. ...
Blind Source Separation (BSS) is a popular research topic in the area of wireless communication. With the fast development of mobile computing, BSS has been widely used in the mobile signal analysis. ...
doi:10.1155/2018/5048419
fatcat:fqoxfgm66zbnpfsu3mtgwa2hcq
Unsupervised Learning based Modified C- ICA for Audio Source Separation in Blind Scenario
2016
International Journal of Information Technology and Computer Science
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The task of source separation becomes trickier when there is no idea about mixing environment and can be termed as blind audio source separation (BASS). ...
Separating audio sources from a convolutive mixture of signals from various independent sources is a very fascinating area in personal and professional context. ...
So, it can be adapted as a better Blind Audio Source Separation Technique. In this analysis effect of noise component is not taken into consideration, if there is noise contamination in mixed signal. ...
doi:10.5815/ijitcs.2016.03.02
fatcat:346wb4p2ebb6poyyipi5g4xgiu
Page 8036 of Mathematical Reviews Vol. , Issue 2003j
[page]
2003
Mathematical Reviews
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fast complex-valued adaptive filtering algorithm. ...
Summary: “A fast complex-valued adaptive filtering algorithm based on the Euclidean direction set (EDS) method is presented in this paper. ...
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