Zaloguj się

Gotowe bibliografie tematyczne / Blind source separation / Artykuły w czasopismach

Kliknij ten link, aby zobaczyć inne rodzaje publikacji na ten temat: Blind source separation.

Artykuły w czasopismach na temat „Blind source separation”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 9 czerwca 2025

Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych

Wybierz rodzaj źródła:

Sprawdź 50 najlepszych artykułów w czasopismach naukowych na temat „Blind source separation”.

Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.

Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.

Przeglądaj artykuły w czasopismach z różnych dziedzin i twórz odpowiednie bibliografie.

1

x, Ekta, and Shelej Khera. "Acoustic Echo Canceller with Blind Source Separation." International Journal of Scientific Engineering and Research 3, no. 6 (June 27, 2015): 83–85. https://doi.org/10.70729/ijser15265.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

2

Zhang, Chao Zhu, Ahmed Kareem Abdullah, and Ali Abdullabs Abdullah. "Electroencephalogram-Artifact Extraction Enhancement Based on Artificial Intelligence Technique." Journal of Biomimetics, Biomaterials and Biomedical Engineering 27 (May 2016): 77–91. http://dx.doi.org/10.4028/www.scientific.net/jbbbe.27.77.

Pełny tekst źródła

Streszczenie:

Blind source separation (BSS) is an important technique used to recover isolated independent sources signals from mixtures. This paper proposes two blind artificial intelligent separation algorithms based on hybridization between artificial intelligent techniques with classical blind source separation algorithms to enhance the separation process. Speedy genetic algorithm SGA directly guesses the optimal coefficients of the separating matrix based on candidate initial from classical BSS algorithms also the separation criteria based on minimization of mutual information between the separating independent components. The proposed algorithms are tested by real Electroencephalogram (EEG) data, the experimental results indicate that the algorithms can quickly and effectively get optimum solution to linear blind source separation compared to classical BSS techniques, the proposed works are described by high accuracy and robustness.

Style APA, Harvard, Vancouver, ISO itp.

3

Frikel, Miloud, Victor Barroso, and Joao Xavier. "Blind source separation." Journal of the Acoustical Society of America 105, no. 2 (February 1999): 1101–2. http://dx.doi.org/10.1121/1.425160.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

4

Behr, Merle, Chris Holmes, and Axel Munk. "Multiscale blind source separation." Annals of Statistics 46, no. 2 (April 2018): 711–44. http://dx.doi.org/10.1214/17-aos1565.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

5

Bachoc, François, Marc G. Genton, Klaus Nordhausen, Anne Ruiz-Gazen, and Joni Virta. "Spatial blind source separation." Biometrika 107, no. 3 (February 17, 2020): 627–46. http://dx.doi.org/10.1093/biomet/asz079.

Pełny tekst źródła

Streszczenie:

Summary Recently a blind source separation model was suggested for spatial data, along with an estimator based on the simultaneous diagonalization of two scatter matrices. The asymptotic properties of this estimator are derived here, and a new estimator based on the joint diagonalization of more than two scatter matrices is proposed. The asymptotic properties and merits of the novel estimator are verified in simulation studies. A real-data example illustrates application of the method.

Style APA, Harvard, Vancouver, ISO itp.

6

Kemiha, Mina, and Abdellah Kacha. "Complex Blind Source Separation." Circuits, Systems, and Signal Processing 36, no. 11 (March 28, 2017): 4670–87. http://dx.doi.org/10.1007/s00034-017-0539-0.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

7

Xu, Jiarui. "Application of blind source separation in sound source separation." Journal of Physics: Conference Series 1345 (November 2019): 032006. http://dx.doi.org/10.1088/1742-6596/1345/3/032006.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

8

Yang, Xiao Yan, Xiong Zhou, and Yi Ke Tang. "A New Method for Adaptive Blind Source Separation Based on the Estimated Number of Dynamic Fault Sources." Applied Mechanics and Materials 233 (November 2012): 211–17. http://dx.doi.org/10.4028/www.scientific.net/amm.233.211.

Pełny tekst źródła

Streszczenie:

In fault diagnosis of large rotating machinery, the number of fault sources may be subject to dynamic changes, which often lead to the failure in accurate estimation of the number of sources and the effective isolation of the fault source. This paper introduced the expansion of the fourth-order cumulant matrices in estimating the dynamic fault source number, plus the relationship between the source signal number and the number of sensors being utilized in the selection of the blind source separation algorithm to achieve adaptive blind source separation. Experiments showed that the source number estimation algorithm could be quite effective in estimating the dynamic number of fault sources, even in the underdetermined condition. This adaptive blind source separation algorithm could then effectively achieve fault diagnosis in respect to the positive-determined, overdetermined and underdetermined blind source separation.

Style APA, Harvard, Vancouver, ISO itp.

9

Yu, Wen, and Wei Chen. "Smart Noise Jamming Suppression Technique Based on Blind Source Separation." International Journal of Signal Processing Systems 7, no. 1 (March 2019): 14–19. http://dx.doi.org/10.18178/ijsps.7.1.14-19.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

10

Chen, Lingguang, Sean F. Wu, Yong Xu, William D. Lyman, and Gaurav Kapur. "Blind Separation of Heart Sounds." Journal of Theoretical and Computational Acoustics 26, no. 01 (March 2018): 1750035. http://dx.doi.org/10.1142/s2591728517500359.

Pełny tekst źródła

Streszczenie:

This paper presents a theoretical foundation for the newly developed methodology that enables the prediction of blood pressures based on the heart sounds measured directly on the chest of a patient. The key to this methodology is the separation of heart sounds into first heart sound and second heart sound, from which components attributable to four heart valves, i.e.: mitral; tricuspid; aortic; and pulmonary valve-closure sounds are separated. Since human physiology and anatomy can vary among people and are unknown a priori, such separation is called blind source separation. Moreover, the sources locations, their surroundings and boundary conditions are unspecified. Consequently, it is not possible to obtain an exact separation of signals. To circumvent this difficulty, we extend the point source separation method in this paper to an inhomogeneous fluid medium, and further combine it with iteration schemes to search for approximate source locations and signal propagation speed. Once these are accomplished, the signals emitted from individual sources are separated by deconvoluting mixed signals with respect to the identified sources. Both numerical simulation example and experiment have demonstrated that this approach can provide satisfactory source separation results.

Style APA, Harvard, Vancouver, ISO itp.

11

Amari, S. "Superefficiency in blind source separation." IEEE Transactions on Signal Processing 47, no. 4 (April 1999): 936–44. http://dx.doi.org/10.1109/78.752592.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

12

Chenot, Cecile, Jerome Bobin, and Jeremy Rapin. "Robust Sparse Blind Source Separation." IEEE Signal Processing Letters 22, no. 11 (November 2015): 2172–76. http://dx.doi.org/10.1109/lsp.2015.2463232.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

13

Wang, Chunli, Quanyu Wang, and Yuping Cao. "Blind source separation of indoor mobile voice sources." Mathematical Modelling of Engineering Problems 4, no. 4 (December 30, 2017): 179–83. http://dx.doi.org/10.18280/mmep.040407.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

14

Nadal, J. P., and E. Korutcheva. "Blind source separation of sources with different magnitudes." Computer Physics Communications 121-122 (September 1999): 707. http://dx.doi.org/10.1016/s0010-4655(06)70111-4.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

15

liang, Yanxue, and Ichiro Hagiwara. "2003 Source Identification Using Blind Source Separation." Proceedings of the JSME annual meeting 2006.1 (2006): 5–6. http://dx.doi.org/10.1299/jsmemecjo.2006.1.0_5.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

16

Rai, C. S., and Yogesh Singh. "Source distribution models for blind source separation." Neurocomputing 57 (March 2004): 501–5. http://dx.doi.org/10.1016/j.neucom.2004.01.003.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

17

Ding-li, CHU, CHEN Hong, and CHEN Han-yi. "Blind Source Separation based on Whale Optimization Algorithm." MATEC Web of Conferences 173 (2018): 03052. http://dx.doi.org/10.1051/matecconf/201817303052.

Pełny tekst źródła

Streszczenie:

Aiming at the problem of linear instantaneous aliasing in blind source separation, a new method of blind signal separation using whale optimization algorithm is proposed in this paper, which provides a new research idea and method for blind signal separation. The new method adopts the method of independent component analysis, optimizes the objective function by using the whale optimization algorithm, realizes the blind separation of instantaneous aliasing signals, and effectively avoids the problem of complex parameters and slow convergence rate of the particle swarm optimization algorithm. The simulation results show that the performance of whale optimization algorithm is better than that of particle swarm optimization for blind source separation, and it is effective for blind signal separation.

Style APA, Harvard, Vancouver, ISO itp.

18

Cheng, Hao, Na Yu, and Jun Liu. "Improved Natural Gradient Algorithms for Multi-Channel Signal Separation." Applied Mechanics and Materials 651-653 (September 2014): 2326–30. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.2326.

Pełny tekst źródła

Streszczenie:

In this paper, an Multi-channel blind separation of Direct Sequence Code Division Multiple Access (DS-CDMA) has been introduced. Most of which we assume statistically stationary sources as well as instantaneous mixtures of signals using blind source separation (BSS) algorithms. In practicality, the CDMA sources received are convolute mixing. A more complex blind separation algorithm is required to achieve better source separation. Based on the minimizing the average squared cross-output-channel-correlation, the proposed scheme obtains the better source separation. Simulation results show that the proposed optimal scheme not only achieves superior bit error rate (BER) performance to those of the existing ones, but also provides a guaranteed-convergent solution under different channel conditions.

Style APA, Harvard, Vancouver, ISO itp.

19

Qian, Si Chong, and Yang Xiang. "The Relationship between Frequency Domain Blind Source Separation and Frequency Domain Adaptive Beamformer." Applied Mechanics and Materials 490-491 (January 2014): 654–62. http://dx.doi.org/10.4028/www.scientific.net/amm.490-491.654.

Pełny tekst źródła

Streszczenie:

As two important methods of array signal processing, blind source separation and beamforming can extract the target signal and suppress interference by using the received information of the array element. In the case of convolution mixture of sources, frequency domain blind source separation and frequency domain adaptive beamforming have similar signal model. To find the relationship between them, comparison between the minimization of the off-diagonal components in the BSS update equation and the minimization of the mean square error in the ABF had been made from the perspective of mathematical expressions, and find that the unmixing matrix of the BSS and the filter coefficients of the ABF converge to the same solution in the mean square error sense under the condition that the two source signals are ideally independent. With MATLAB, the equivalence in the frequency domain have been verified and the causes affecting separation performance have been analyzed, which was achieved by simulating instantaneous and convolution mixtures and separating mixture speech in frequency-domain blind source separation and frequency domain adaptive beamforming way.

Style APA, Harvard, Vancouver, ISO itp.

20

Zhao, Zhi Jin, and Zhong Jian Liu. "Mixed NMF Blind Source Separation Algorithm." Applied Mechanics and Materials 596 (July 2014): 169–73. http://dx.doi.org/10.4028/www.scientific.net/amm.596.169.

Pełny tekst źródła

Streszczenie:

The rank one NMF blind source separation algorithm (NMF-R1) was obtained by imposing the sparsity constraint on the fast NMF algorithm based rank one. NMF blind source separation algorithm based on least squares (NMF-LS) was obtained by using pseudo-inverse matrix. NMF-R1 algorithm was superior to the existing blind source separation algorithms based on NMF. NMF-LS algorithm had faster computation speed, but the result of decomposition was not unique. In order to further enhance the signals separated performance, crossover iteration between NMF-R1 and NMF-LS was used to getting the mixing matrix and the signal matrix, and the mixed NMF blind source separation algorithm (NMF-LR) was obtained. Simulation results show that the separation performance of NMF-LR algorithm is better than that of NMF-R1 and NMF-LS, and the computation complexity of NMF-LR algorithm is nearly the same as NMF-R1 algorithm.

Style APA, Harvard, Vancouver, ISO itp.

21

Tang, Mingyang, and Yafeng Wu. "A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search." Sensors 23, no. 19 (October 8, 2023): 8325. http://dx.doi.org/10.3390/s23198325.

Pełny tekst źródła

Streszczenie:

Currently, the widely used blind source separation algorithm is typically associated with issues such as a sluggish rate of convergence and unstable accuracy, and it is mostly suitable for the separation of independent source signals. Nevertheless, source signals are not always independent of one another in practical applications. This paper suggests a blind source separation algorithm based on the bounded component analysis of the enhanced Beetle Antennae Search algorithm (BAS). Firstly, the restrictive assumptions of the bounded component analysis method are more relaxed and do not require the signal sources to be independent of each other, broadening the applicability of this blind source separation algorithm. Second, the objective function of bounded component analysis is optimized using the improved Beetle Antennae Search optimization algorithm. A step decay factor is introduced to ensure that the beetle does not miss the optimal point when approaching the target, improving the optimization accuracy. At the same time, since only one beetle is required, the optimization speed is also improved. Finally, simulation experiments show that the algorithm can effectively separate independent and dependent source signals and can be applied to blind source separation of images. Compared to traditional blind source separation algorithms, it has stronger universality and has faster convergence speed and higher accuracy compared to the original independent component analysis algorithm.

Style APA, Harvard, Vancouver, ISO itp.

22

Li, Zhi Nong, Fen Zhang, Xu Ping He, and Yao Xian Xiao. "Application of the Blind Source Separation Based on Time-Frequency Analysis in Mechanical Fault Diagnosis." Advanced Materials Research 945-949 (June 2014): 1054–62. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.1054.

Pełny tekst źródła

Streszczenie:

Blind source separation provides a new method for the separation of mechanical sources under high level background noise, as well as the diagnosis of the compound fault. At present, the blind source separation has been successfully applied to the mecanical fault diagnosis. But the traditional mechanical source separation methods are restricted to non-gauss, stationary and mutually independent source signals. However, the mechanical fault signals do not suffice to these conditions, and generally exhibit non-stationarity and non-independence. For the non-stationary signal, its spectral feature is time-varying. Thus only the time-domain or frequency-domain analysis is not sufficient to describe the characteristics of non-stationary signal. The time-frequency analysis, which can provide the information about that the spectrum of the signal varies with the time, is a useful tool for non-stationary signal analysis. In this paper, combined time-frequency analysis with blind source separation, a blind source separation method for the non-stationary signal of the mechanical equipment based on time-frequency analysis is proposed and studied. The simulation and experimental results show that the proposed approach is feasible and effective.

Style APA, Harvard, Vancouver, ISO itp.

23

Yang, Zuyuan, Yong Xiang, Yue Rong, and Kan Xie. "A Convex Geometry-Based Blind Source Separation Method for Separating Nonnegative Sources." IEEE Transactions on Neural Networks and Learning Systems 26, no. 8 (August 2015): 1635–44. http://dx.doi.org/10.1109/tnnls.2014.2350026.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

24

Yu, Yang, and Xiang Zhou. "Study on Corrosion Acoustic Emission Separation Based on Blind Source Separation." Advanced Materials Research 503-504 (April 2012): 1597–600. http://dx.doi.org/10.4028/www.scientific.net/amr.503-504.1597.

Pełny tekst źródła

Streszczenie:

When corrosion signals of tank bottom is detected by online method, it is essential to identify corrosion signals of different corrosion pots. It is a new method based on blind source separation. Blind source separation has produced many arithetics, among which entropy maximization is more mature. The aim of this paper is to separate corrosion signals by using entropy maximization arithmetic. Furthermore, the separation of linear mixed acoustic emission signals is achieved through simulation. The results indicate that blind source separation is an effective method for the separation of corrosion signals.

Style APA, Harvard, Vancouver, ISO itp.

25

Todorovic-Zarkula, Slavica, Branimir Todorovic, and Miomir Stankovic. "On-line blind separation of non-stationary signals." Yugoslav Journal of Operations Research 15, no. 1 (2005): 79–95. http://dx.doi.org/10.2298/yjor0501079t.

Pełny tekst źródła

Streszczenie:

This paper addresses the problem of blind separation of non-stationary signals. We introduce an on-line separating algorithm for estimation of independent source signals using the assumption of non-stationary of sources. As a separating model, we apply a self-organizing neural network with lateral connections, and define a contrast function based on correlation of the network outputs. A separating algorithm for adaptation of the network weights is derived using the state-space model of the network dynamics, and the extended Kalman filter. Simulation results obtained in blind separation of artificial and real-world signals from their artificial mixtures have shown that separating algorithm based on the extended Kalman filter outperforms stochastic gradient based algorithm both in convergence speed and estimation accuracy.

Style APA, Harvard, Vancouver, ISO itp.

26

Keziou, A., H. Fenniri, A. Ghazdali, and E. Moreau. "New blind source separation method of independent/dependent sources." Signal Processing 104 (November 2014): 319–24. http://dx.doi.org/10.1016/j.sigpro.2014.04.017.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

27

Mourad, Nasser, James P. Reilly, and T. Kirubarajan. "Majorization–minimization for blind source separation of sparse sources." Signal Processing 131 (February 2017): 120–33. http://dx.doi.org/10.1016/j.sigpro.2016.08.015.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

28

Nadal, J. P., E. Korutcheva, and F. Aires. "Blind source separation in the presence of weak sources." Neural Networks 13, no. 6 (July 2000): 589–96. http://dx.doi.org/10.1016/s0893-6080(00)00041-1.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

29

Lei, Yan Bin, Zhi Gang Chen, and Hai Ou Liu. "Blind Separation Method for Gearbox Mixed Fault Signals." Applied Mechanics and Materials 86 (August 2011): 180–83. http://dx.doi.org/10.4028/www.scientific.net/amm.86.180.

Pełny tekst źródła

Streszczenie:

A new blind source separation (BSS) algorithm used for separating mixed gearbox signals is proposed in this paper. Firstly, whiten the observed signals, and then diagonalize the second- and higher-order cumulant matrix to get an orthogonal separation matrix. The feasibility of the algorithm is validated through separating the mechanical simulation signals and the gearbox vibration signals. The algorithm can successfully identified the failure source of the gearbox and provides a new method to a gearbox fault.

Style APA, Harvard, Vancouver, ISO itp.

30

Liu, Qiong, Hao Peng, and Haitao Wang. "Intelligent particle blind source separation research." Journal of Computational Methods in Sciences and Engineering 18, no. 2 (May 3, 2018): 319–27. http://dx.doi.org/10.3233/jcm-180791.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

31

Ghazdali, Abdelghani, Abdelmoutalib Metrane, and Amal Ourdou. "Blind Source Separation for Text Mining." Journal of Physics: Conference Series 1743 (January 2021): 012018. http://dx.doi.org/10.1088/1742-6596/1743/1/012018.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

32

Martinez, D., and A. Bray. "Nonlinear blind source separation using kernels." IEEE Transactions on Neural Networks 14, no. 1 (January 2003): 228–35. http://dx.doi.org/10.1109/tnn.2002.806624.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

33

ZHANG, Xianda. "Grading learning for blind source separation." Science in China Series F 46, no. 1 (2003): 31. http://dx.doi.org/10.1360/03yf9003.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

34

Xi-Ren Cao and Ruey-Wen Liu. "General approach to blind source separation." IEEE Transactions on Signal Processing 44, no. 3 (March 1996): 562–71. http://dx.doi.org/10.1109/78.489029.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

35

Shun-Ichi Amari and J. F. Cardoso. "Blind source separation-semiparametric statistical approach." IEEE Transactions on Signal Processing 45, no. 11 (1997): 2692–700. http://dx.doi.org/10.1109/78.650095.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

36

Shi, Z., and C. Zhang. "Energy predictability to blind source separation." Electronics Letters 42, no. 17 (2006): 1006. http://dx.doi.org/10.1049/el:20061456.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

37

Stone, James V. "Blind Source Separation Using Temporal Predictability." Neural Computation 13, no. 7 (July 1, 2001): 1559–74. http://dx.doi.org/10.1162/089976601750265009.

Pełny tekst źródła

Streszczenie:

A measure of temporal predictability is defined and used to separate linear mixtures of signals. Given any set of statistically independent source signals, it is conjectured here that a linear mixture of those signals has the following property: the temporal predictability of any signal mixture is less than (or equal to) that of any of its component source signals. It is shown that this property can be used to recover source signals from a set of linear mixtures of those signals by finding an un-mixing matrix that maximizes a measure of temporal predictability for each recovered signal. This matrix is obtained as the solution to a generalized eigenvalue problem; such problems have scaling characteristics of O (N3), where N is the number of signal mixtures. In contrast to independent component analysis, the temporal predictability method requires minimal assumptions regarding the probability density functions of source signals. It is demonstrated that the method can separate signal mixtures in which each mixture is a linear combination of source signals with supergaussian, sub-gaussian, and gaussian probability density functions and on mixtures of voices and music.

Style APA, Harvard, Vancouver, ISO itp.

38

Harmeling, Stefan, Andreas Ziehe, Motoaki Kawanabe, and Klaus-Robert Müller. "Kernel-Based Nonlinear Blind Source Separation." Neural Computation 15, no. 5 (May 1, 2003): 1089–124. http://dx.doi.org/10.1162/089976603765202677.

Pełny tekst źródła

Streszczenie:

We propose kTDSEP, a kernel-based algorithm for nonlinear blind source separation (BSS). It combines complementary research fields: kernel feature spaces and BSS using temporal information. This yields an efficient algorithm for nonlinear BSS with invertible nonlinearity. Key assumptions are that the kernel feature space is chosen rich enough to approximate the nonlinearity and that signals of interest contain temporal information. Both assumptions are fulfilled for a wide set of real-world applications. The algorithm works as follows: First, the data are (implicitly) mapped to a high (possibly infinite)—dimensional kernel feature space. In practice, however, the data form a smaller submanifold in feature space—even smaller than the number of training data points—a fact that has already been used by, for example, reduced set techniques for support vector machines. We propose to adapt to this effective dimension as a preprocessing step and to construct an orthonormal basis of this submanifold. The latter dimension-reduction step is essential for making the subsequent application of BSS methods computationally and numerically tractable. In the reduced space, we use a BSS algorithm that is based on second-order temporal decorrelation. Finally, we propose a selection procedure to obtain the original sources from the extracted nonlinear components automatically. Experiments demonstrate the excellent performance and efficiency of our kTDSEP algorithm for several problems of nonlinear BSS and for more than two sources.

Style APA, Harvard, Vancouver, ISO itp.

39

Rasaily, Deepak, Rajesh Mehra, and Naveen Dubey. "Divergence for Blind Audio Source Separation." International Journal of Computer Trends and Technology 28, no. 1 (October 25, 2015): 1–4. http://dx.doi.org/10.14445/22312803/ijctt-v28p101.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

40

Zhou, Yi, and Boling Xu. "Blind source separation in frequency domain." Signal Processing 83, no. 9 (September 2003): 2037–46. http://dx.doi.org/10.1016/s0165-1684(03)00134-8.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

41

Singh, Yogesh, and C. S. Rai. "Blind source separation: a unified approach." Neurocomputing 49, no. 1-4 (December 2002): 435–38. http://dx.doi.org/10.1016/s0925-2312(02)00672-0.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

42

Even, Jani, and Eric Moisan. "Blind source separation using order statistics." Signal Processing 85, no. 9 (September 2005): 1744–58. http://dx.doi.org/10.1016/j.sigpro.2005.04.001.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

43

Kumar, M., and V. E. Jayanthi. "Underdetermined blind source separation using CapsNet." Soft Computing 24, no. 12 (October 15, 2019): 9011–19. http://dx.doi.org/10.1007/s00500-019-04430-4.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

44

Shi, Zhenwei, and Changshui Zhang. "Nonlinear innovation to blind source separation." Neurocomputing 71, no. 1-3 (December 2007): 406–10. http://dx.doi.org/10.1016/j.neucom.2007.08.007.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

45

Grosse-Wentrup, M., and M. Buss. "Subspace identification through blind source separation." IEEE Signal Processing Letters 13, no. 2 (February 2006): 100–103. http://dx.doi.org/10.1109/lsp.2005.861581.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

46

Thi, Hoang-Lan Nguyen, and Christian Jutten. "Blind source separation for convolutive mixtures." Signal Processing 45, no. 2 (August 1995): 209–29. http://dx.doi.org/10.1016/0165-1684(95)00052-f.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

47

Rowlands, Christopher J., and Stephen R. Elliott. "Improved blind-source separation for spectra." Journal of Raman Spectroscopy 42, no. 9 (March 31, 2011): 1761–68. http://dx.doi.org/10.1002/jrs.2936.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

48

Le, Thanh Trung, Karim Abed-Meraim, Philippe Ravier, Olivier Buttelli, and Ales Holobar. "Tensor decomposition meets blind source separation." Signal Processing 221 (August 2024): 109483. http://dx.doi.org/10.1016/j.sigpro.2024.109483.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

49

Li, Ning, Hai Ting Chen, and Shao Peng Liu. "Rotating Machine Monitoring Based on Blind Source Separation of Correlated Source Signals." Applied Mechanics and Materials 321-324 (June 2013): 1299–302. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.1299.

Pełny tekst źródła

Streszczenie:

Blind source separation (BSS) which separate the unknown sources from the observed signals is a new signal processing technique. The most methods for solving this problem rely on assumptions of independence or uncorrelation of source signals at least. However, the observed signal is always interfered by signals with common frequency in the rotating machine, and difficult to be separated by the conventional BSS method. In this paper, it is proved that the source signals with common frequencies are correlative, and the separating error brought by the cross-correlation of the source signals is analyzed. A new separating method for the correlated source signals with frequency overlapping is presented and it is successfully applied to separate the monitoring signals of rotor test stand.

Style APA, Harvard, Vancouver, ISO itp.

50

Liu, Jian-Qiang, Da-Zheng Feng, and Wei-Wei Zhang. "Adaptive Improved Natural Gradient Algorithm for Blind Source Separation." Neural Computation 21, no. 3 (March 2009): 872–89. http://dx.doi.org/10.1162/neco.2008.07-07-562.

Pełny tekst źródła

Streszczenie:

We propose an adaptive improved natural gradient algorithm for blind separation of independent sources. First, inspired by the well-known backpropagation algorithm, we incorporate a momentum term into the natural gradient learning process to accelerate the convergence rate and improve the stability. Then an estimation function for the adaptation of the separation model is obtained to adaptively control a step-size parameter and a momentum factor. The proposed natural gradient algorithm with variable step-size parameter and variable momentum factor is therefore particularly well suited to blind source separation in a time-varying environment, such as an abruptly changing mixing matrix or signal power. The expected improvement in the convergence speed, stability, and tracking ability of the proposed algorithm is demonstrated by extensive simulation results in both time-invariant and time-varying environments. The ability of the proposed algorithm to separate extremely weak or badly scaled sources is also verified. In addition, simulation results show that the proposed algorithm is suitable for separating mixtures of many sources (e.g., the number of sources is 10) in the complete case.

Style APA, Harvard, Vancouver, ISO itp.

Oferujemy zniżki na wszystkie plany premium dla autorów, których prace zostały uwzględnione w tematycznych zestawieniach literatury. Skontaktuj się z nami, aby uzyskać unikalny kod promocyjny!