毕业论文

打赏
当前位置: 毕业论文 > 文献综述 >

声源定位技术文献综述和英文参考文献

时间:2018-11-22 15:23来源:毕业论文
声源定位在各个领域都有着广泛的应用,早在20世纪七八十年代,声源定位系统就开始被广泛地研究,尤其是基于传感器阵列的方法。它的应用使得电话会议、视频会议、可视电话等系统

声源定位在各个领域都有着广泛的应用,早在20世纪七八十年代,声源定位系统就开始被广泛地研究,尤其是基于传感器阵列的方法。它的应用使得电话会议、视频会议、可视电话等系统中摄像头和传声器能够对准正在说话的人。30471
声源定位技术在经过几十年的发展后,其检测技术已经有了极大程度的发展和提高。由最早的基于碳粒子或冷凝器来接收声信号的模式的普通声波检测技术发展到如今基于电路集成化与电子信息化结合的声源检测技术。现代的声源定位现代技术测量过程简化了,而检测精度提高了。 论文网
  国外的声波检测技术已经在坦克和武装直升机上得到了广泛的应用,而在这方面,传感器技术、探测技术、微电子技术、信号处理技术以及人工智能技术的飞速发展,均为声源探测技术用于直升机等军事目标的定位、跟踪和识别开辟了新的应用前景,使声源探测技术成为一种重要的军事侦察手段和防空作战中反电子干扰和反低空突防的一种有效途径。当然国内在这方面的研究也是逐步与国际接轨。近年来,具有广阔的应用前景和实际意义的声源定位技术已成为新的研究热点,不仅仅是在军事上,许多国际著名公司和研究机构已经在声源定位技术研究与应用上开始了新的角力,许多产品已进入实际应用阶段。并且已经显示出巨大的优势和市场潜力。
参考文献
[1]    Oyilmaz,S.Rickard. Blind Separation of Speech Mixtures via Time-Frequency Masking[J]. IEEE Transactions on Signal Processing, 2004, 52(7):1830-1847.
[2]    H. Sawada, S. Araki, R. Mukai, S. Makino. Blind extraction of dominant target sources using ICA and time-frequency masking[J]. IEEE Transactions on Audio, Speech, and Language Processing , 2006, 14 (6): 2165–2173.
[3]    M.Swartling,N.Grbic´, I.Claesson. Direction of arrival estimation for multiple speakers using time-frequency orthogonal signal separation[C]. Proceedings of IEEE International Conference on acoustic, Speech and Signal Processing, 2006. 833–836.
[4]    M. S. Brand stein, J.E. Adcock, H.F. Silverman. A closed-form location estimator for use with room environment microphone arrays[J]. IEEE Transactions on Speech and Audio Processing, 1997, 5 (1): 45–50.
[5]    M. Swartling, M. Nilsson, N.Grbic. Distinguishing true and false source locations when localizing multiple concurrent speech sources[C]. Proceedings of IEEE Sensor Array and Multichannel Signal ProcessingWorkshop, 2008. 361–364.
[6]    E. Di Claudio, R. Parisi, G. Orlandi. Multi-source localization in reverberant environments by ROOT-MUSIC and clustering[C]. Proceedings of IEEE International Conference on Acoustic, Speech and Signal Processing, 2000. 921–924.
[7]    T. Nishiura, T. Yamada, S. Nakamura, K. Shikano. Localization of multiple sound sources based on a CSP analysis with a microphone array[C]. Proceedings of IEEE International Conference on Acoustic, Speech and Signal Processing, 2000. 1053–1056.
[8]    R. Balan, J. Rosca, S. Rickard, J. ORuanaidh. The influence of windowing of time delay estimates[C]. Proceedings of Conference on Information Sciences and Systems, 2000. 15–17.
[9]    S. Shifman, A. Bhomra, S. Smiley, et al. A whole genome association study of neuroticism using DNA pooling[J]. Molecular Psychiatry, 2008, 13(3): 302–312.
[10]    S. Rickard, R. Balan, J. Rosca, Real-time time-frequency based blind source separation[C]. Proceedings of International Workshop on Independent Component Analysis and Blind Signal Separation, 2001. 651–656.
[11]    K. Yiu, N. Grbic, S. Nordholm, et al. Multi-criteria design of oversampled uniform DFT filterbanks[J]. IEEE Signal Processing Letters, 2004, 11(6): 541–544.
[12]    E. Vincent. Complex nonconvex lp nom minimization for underdetermined source separation[C]. Proc. ICA, 2007. 430-437
[13]    C. Knapp , G. Carter. The generalized correlation method for estimation of time delay[J]. IEEE Trans. Acoust., Speech, Signal Process, 1987, 24(4): 320–327.
[14]    T. W. Anderson. Asymptotic theory for principal component analysis[J]. Ann. Math. Statist., 2009, 34(1): 122–148.
[15]    D. Campbell, K. Palomäki, G. Brown. A matlab simulation of shoebox room acoustics for use in research and teaching[J]. Comput. Inf. Syst. J., 2010, 9(3): 48–51
[16]    J. Huang, N. Ohnishi, N. Sugie. A biomimetic system for localization and separation of multiple sound sources[J]. IEEE Trans. Instrum.Meas., 1995(44): 733–738.
[17]    B. Berdugo, J. Rosenhouse, H. Azhari. Speakers’ direction finding using estimated time delays in the frequency domain[J]. Signal Processing, 2002, 82(1): 19–30.
[18]    S. T. Roweis. One microphone source separation[J]. Neural Inform.Process. Syst., 793–799.
[19]    J.-K. Lin, D. G. Grier, J. D. Cowan. Feature extraction approachto blind source separation[C]. Proc. IEEE Workshop Neural NetworksSignal Process, 1997. 398–405.
[20]    M. Van Hulle. Clustering approach to square and nonsquare blind source separation[C]. IEEE Workshop Neural Networks Signal Processing. 1999. 315–323. 声源定位技术文献综述和英文参考文献:http://www.751com.cn/wenxian/lunwen_26196.html
------分隔线----------------------------
推荐内容