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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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2016-Dec-17
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  4/2013 - 6

Microphone Clustering and BP Network based Acoustic Source Localization in Distributed Microphone Arrays

ZHANG, Q. See more information about ZHANG, Q. on SCOPUS See more information about ZHANG, Q. on IEEExplore See more information about ZHANG, Q. on Web of Science, CHEN, Z. See more information about  CHEN, Z. on SCOPUS See more information about  CHEN, Z. on SCOPUS See more information about CHEN, Z. on Web of Science, YIN, F. See more information about YIN, F. on SCOPUS See more information about YIN, F. on SCOPUS See more information about YIN, F. on Web of Science
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (812 KB) | Citation | Downloads: 334 | Views: 2,119

Author keywords
acoustic source localization, BP neural network, microphone clustering, GCC-PHAT, TDOA

References keywords
processing(17), signal(14), source(11), speech(9), microphone(9), sound(8), localization(8), estimation(7), acoustics(7), network(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-11-30
Volume 13, Issue 4, Year 2013, On page(s): 33 - 40
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.04006
Web of Science Accession Number: 000331461300006
SCOPUS ID: 84890239023

Abstract
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A microphone clustering and back propagation (BP) neural network based acoustic source localization method using distributed microphone arrays in an intelligent meeting room is proposed. In the proposed method, a novel clustering algorithm is first used to divide all microphones into several clusters where each one corresponds to a specified BP network. Afterwards, the energy-based cluster selecting scheme is applied to select clusters which are small and close to the source. In each chosen cluster, the time difference of arrival of each microphone pair is estimated, and then all estimated time delays act as input of the corresponding BP network for position estimation. Finally, all estimated positions from the chosen clusters are fused for global position estimation. Only subsets rather than all the microphones are responsible for acoustic source localization, which leads to less computational cost; moreover, the local estimation in each selected cluster can be processed in parallel, which expects to improve the localization speed potentially. Simulation results from comparison with other related localization approaches confirm the validity of the proposed method.


References | Cited By  «-- Click to see who has cited this paper

[1] M. R. Bai, C. Lin, "Microphone array signal processing with application in three-dimensional spatial hearing", The Journal of the Acoustical Society of America, vol. 117, no. 4, pp. 2112-2121, Apr. 2005.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 7]


[2] Z. Zhang, A. G. Andreou, "Slow moving vehicles using the microphone arrays in the Hopkins acoustic surveillance unit", Micro-Nanoelectronics, Technology and Applications, pp. 140-143, Buenos Aires, Argentina, Sept. 2008.

[3] Z. W. Yu, Z. Y. Yu, H. Aoyama, M. Ozeki, Y. Nakamura, "Capture, recognition, and visualization of human semantic interactions in meetings", IEEE International Conference on Pervasive Computing and Communications (PerCom), pp. 107-115, Mannheim, German, March-April 2010.
[CrossRef]


[4] C. Zhang, D. Florencio, D. E. Ba, Z. Zhang, "Maximum likelihood sound source localization and beam-forming for directional microphone arrays in distributed meetings", IEEE Transaction on Pervasive Computing and Communications, vol. 10, no. 3, pp. 538-548, Apr. 2008.
[CrossRef] [Web of Science Times Cited 62] [SCOPUS Times Cited 91]


[5] J. Benesty, Y. Huang, and J. Chen, "Time delay estimation via minimum entropy", IEEE Signal Processing Letters, vol. 14, no. 3, pp. 157-160, Mar. 2007.
[CrossRef] [Web of Science Times Cited 32] [SCOPUS Times Cited 48]


[6] R. Roy, A. Paulraj, T. Kailath, "Direction-of-arrival estimation by subspace rotation methods - ESPRIT", IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP, vol. 11, pp. 2495-2498, Tokyo, Japan, Apr. 1986.
[CrossRef]


[7] D. R. Farrier , "Direction of arrival estimation by subspace methods", IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 5, pp. 2651-2654, Albuquerque, New Mexico, USA, Apr. 1990.
[CrossRef] [Web of Science Record]


[8] M. Cobos, A. Marti, J. Lopez, "A modified SRP-PHAT functional for robust real-time sound source localization with scalable spatial sampling", IEEE Signal Processing Letters, vol. 18, no. 1, Jan. 2011.
[CrossRef] [Web of Science Times Cited 49]


[9] Y. Rui , D. Florencio , W. Lam, J. Su," Sound source localization for circular arrays of directional microphones", IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 3, pp. iii/93-iii/96, Pennsylvania, USA, Mar. 2005.
[CrossRef] [SCOPUS Times Cited 19]


[10] P. Aarabi, "The fusion of distributed microphone arrays for sound localization", EURASIP Journal on Advances in Signal Processing, pp. 338-347, Jan. 2003.
[CrossRef] [SCOPUS Times Cited 76]


[11] E. Elahi, "Sound localization and tracking using distributed microphones fusion: maximum likelihood or maximum a-posteriori approach?", The 2nd International Conference on Computer, Control and Communication, pp. 1-6, Karachi, Pakistan, Feb. 2009.
[CrossRef] [SCOPUS Times Cited 1]


[12] T. Takagi, H. Noguchi, K. Kugata, "Microphone array network for ubiquitous sound acquisition", IEEE International Conference on Acoustics Speech and Signal Processing, pp. 1474-1477, Dallas, Texas, USA, Mar. 2010.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 8]


[13] G. Valenzise, G. Prandi, M. Tagliasacchi, A. Sarti, "Resource constrained efficient acoustic source localization and tracking using a distributed network of microphones", IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2581-2584, Las Vegas, USA, March - April 2008.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 6]


[14] C. Knapp, G. Carter, "The generalized correlation method for estimation of time delay", IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 24, no. 4, pp. 320-327, Aug. 1976.
[CrossRef] [Web of Science Times Cited 1676] [SCOPUS Times Cited 2331]


[15] J. S. Hu, C. H. Yang, C. K. Wang, "Estimation of sound source number and directions under a multi-source environment", IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 181-186, St. Louis, USA, Oct. 2009.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 6]


[16] D. Arthur, S. Vassilvitskii, "k-means++: the advantages of careful seeding", Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1027-1035, PA, USA, 2007.

[17] G. Arslan, F. A. Sakarya, "A unified neural-network-based speaker localization technique", IEEE Transactions on Neural Networks, vol. 11, no. 4, pp. 997-1002, Jul. 2000.
[CrossRef] [Web of Science Times Cited 10] [SCOPUS Times Cited 13]


[18] G. Yang, J. Jongdae, S. Donggug, "Sound-source localization system based on neural network for mobile robots", IEEE International Joint Conference on Neural Networks, IEEE World Congress on Computational Intelligence, pp. 3126-3130, Hong Kong, China, Jun. 2008.
[CrossRef] [Web of Science Record] [SCOPUS Record]


[19] V. H. Dang, T. P. Phan, B. V. Le, Y. K. Lee, "Clustering based multi-object positioning system", International Conference on Advanced Technologies for Communications (ATC), pp. 40-44, Da Nang, Vietnam, Aug. 2011
[CrossRef] [SCOPUS Times Cited 3]


[20] A. Y. Nakano, K. Yamamoto, S. Nakagawa, "Directional acoustic source's position and orientation estimation approach by a microphone array network", IEEE Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, pp. 606-611, Marco Island, Florida, USA, Jan. 2009.
[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 16]


[21] I. Himawan, I. McCpwam, S. Sridharam, "Clustered blind beamforming from Ad-Hoc microphone arrays", IEEE Transactions on Audio, Speech and Language Processing, vol. 19, no. 4, pp. 661-676, May. 2011.
[CrossRef] [Web of Science Times Cited 25] [SCOPUS Times Cited 34]


[22] T. L. Nwe, H. Sun, B. Ma, H. Li, "Speaker clustering and cluster purification methods for RT07 and RT09 Evaluation meeting data", IEEE Transactions on Audio, Speech and Language Processing, vol. 20, no. 2, pp. 461-473, Feb. 2012.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 13]


[23] M. Souden, K. Kinoshita, M. Delcroix, T. Nakatani, "Distributed microphone array processing for speech source separation with classifier fusion", IEEE International Workshop on Machine Leaning for Signal processing (MLSP), pp. 1-6, Santander, Spain, Sept. 2012.
[CrossRef] [SCOPUS Times Cited 11]


[24] H. Chen, C. K. Tse, J. B. Feng, "Minimizing effective energy consumption in multi-cluster sensor network for source extraction", IEEE Transactions on Wireless Communications, vol. 8, no. 3, pp. 1480-1489, Mar. 2009.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 21]


[25] B. R. Dai, J. W. Huang, M. Y. Yeh, M. S. Chen, "Adaptive clustering for multiple evolving streams", IEEE Transactions on Knowledge and Data Engineering, vol. 18, no. 9, pp. 1166-1180, Sept. 2006.
[CrossRef] [Web of Science Times Cited 47] [SCOPUS Times Cited 73]


[26] M. Chen, Z. Liu, L. W. He, P. Chou, Z. Y. Zhang "Energy-based position estimation of microphones and speakers for Ad Hoc microphone arrays", IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 22-25, Honolulu, HI, USA, Oct. 2007.
[CrossRef] [SCOPUS Times Cited 38]


[27] E. A. Lehmann, A. M. Johansson, "Prediction of energy decay in room impulse responses simulated with an image-source model", The Journal of Acoustic Society of America, vol. 124, no. 1, Jun, 2008.
[CrossRef] [Web of Science Times Cited 119] [SCOPUS Times Cited 162]




References Weight

Web of Science® Citations for all references: 2,071 TCR
SCOPUS® Citations for all references: 2,977 TCR

Web of Science® Average Citations per reference: 74 ACR
SCOPUS® Average Citations per reference: 106 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-12-11 20:57 in 152 seconds.




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