互耦多通道自适应有源噪声抵消技术研究
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摘要
潜艇自噪声是被动声纳系统的主要干扰。它使声纳接收端的输入信噪比降低,导致被动声纳的有效作用距离相应减小。因此,降低潜艇的自噪声具有很重要的意义。潜艇降噪是一项系统工程,不但需要巨额投入,还有一系列技术问题尚待取得突破,一时还无法从根本上解决。所以,研究潜艇自噪声的自适应有源抵消技术是十分必要的,具有实际应用价值。本文研究使用声学方法在降低潜艇自噪声的同时保留目标信号的自适应噪声抵消技术。与传统的有源降噪技术相比,技术上有创新性,难度更大。
自适应有源噪声抵消(AANC)技术基于由初级声源产生的声场与次级声源产生的声场相消干涉原理。次级声源的输出可以由控制器控制,这个控制器一般是自适应滤波器。自适应有源噪声抵消系统的核心是自适应滤波器结构和算法。
参考输入中信号分量对自适应有源噪声抵消系统性能影响很大。本文对参考信号中信号分量对AANC系统性能的影响进行了详细的分析,得到自适应滤波器解无约束的条件下,AANC系统输出端信噪比、信号失真度及噪声分量功率谱的计算式,并通过引入模平方相干函数提出衡量AANC系统处理增益的评估方法。
线谱噪声主要集中在自噪声的低频段。本文提出了一种采用切比雪夫多项式的直接并联型结构线谱噪声多通道有源陷波器,并且与直接型结构和并联型结构有源抵消器进行了比较。采用切比雪夫多项式在一定程度上保证了可靠的参考输入,采用直接并联型结构增大了参考输入中各谐波分量之间的频率间隔,提高了收敛速度。同时,本文提出了一种采用单位脉冲串的多通道自适应有源噪声抵消器,将这种有源噪声抵消器和Delayed-X LMS算法相结合,可以大大的减小运算量,并且也可以保证良好的收敛特性。
连续谱噪声属于宽带噪声。本文首先介绍了时域多通道滤波—X最小二乘(MFXRLS)算法,然后重点提出了一种基于线性卷积的频域多通道滤波—X最小二乘(MLFFXRLS)算法。通过理论分析和计算机仿真可以看出,MLFFXRLS
Submarine noise is the main interference of passive sonar system, which decreases the SNR at the input of the passive sonar, resulting in the deduction of sonar ranging. Therefore, reduction of submarine noise is of great importance. The reduction of submarine noise is a systematic project, requiring enormous financial support as well as series of techniques which have not yet been resolved fundamentally up till now so that researches on the techniques of adaptive active submarine noise canceling is meaningful and valuable for practical application. Applying the acoustical principles, our research subject is to find out a new adaptive active noise canceling technique, which will retain the signal energy during the noise canceling process. This technique is creative and much more difficult compared with conventional active adaptive noise canceling.AANC(Adaptive Active Noise Cancellation) works on the principle of destructive interference between the sound fields generated by the original "primary" sound source and that due to other "secondary" sources, whose acoustic outputs can be controlled by controllers, which are usually adaptive filters. The key is the configuration of adaptive filters and the corresponding algorithm in AANC systems.It's great for the effect of the signal components in the reference input on the performance of the AANC systems. In this paper, the effect of the signal components combined with the reference noises on the performance of the AANC systems has been studied comprehensively. Mathematical expressions of the signal-to-noise density ratio, signal distortion and noise power spectrum at the adaptive active noise canceller output have been derived under the condition of no constraints for the adaptive solution. By introducing Modular Squared Coherence(MSC) function to the AANC systems, the method for evaluating the processing gain of the AANC systems is proposed in the paper.
The line noise is a primary low frequency component of self-noise in submarines. In this paper, a hybrid active periodic noise canceller based on Chebyshev Polynomials has been introduced, and it has been compared with the direct form and the parallel form. Using chebyshev polynomials assures reliable reference inputs to a certain extent. The frequency difference between any two successive sinusoidal components is effectively increased in the hybrid form, as compared to the direct implementation technique. The rate of convergence of each adaptive filter can be significantly improved. In this paper, an AANC using a pulse train has been introduced to reduce the line interference. It has been shown that the total computational cost decreases if the AANC is combined with the Delayed-X LMS algorithm, and the excellent convergence performance has been obtained.The continuous power spectrum noise is wideband noise. First, the multi-channel filtered-x recursive-least-squares(MFXRLS) algorithms are introduced in time domain in this paper. Secondly, the frequency domain multi-channel filtered-X recursive least squares based on linear convolution(MLFFXRLS) algorithm has been proposed. It can be seen from the theoretical analysis and computer simulations that the MLFFXRLS algorithm will be have a much lower computational load than the MFXRLS algorithm, and the MLFFXRLS algorithm will be have a lower computational load than the MFXLMS algorithm for large channels numbers. In this paper, a delayless subband multi-channel system for active broadband self-noise canceling is also introduced, which has computational and convergence speed advantages comparable to a conventional subband design but without introducing any delay in the cancellation path.Finally, we analyze the real data using the proposed algorithms in the paper. In the case of uncorrelated signal and noise, whose bandwidths are both 2kHz, it can be shown from the processing that the adaptive processing gain of 21 dB was obtained, applying the MLFFXRLS algorithm, under the conditions of 2 control actuators, 2 error sensors and the perfect transfer functions of the primary paths and secondary paths to a certain extent if SNR
is lower than -45dB in the reference input. The results validate the effectiveness of the proposed algorithms in the practice.
自适应有源噪声抵消(AANC)技术基于由初级声源产生的声场与次级声源产生的声场相消干涉原理。次级声源的输出可以由控制器控制,这个控制器一般是自适应滤波器。自适应有源噪声抵消系统的核心是自适应滤波器结构和算法。
参考输入中信号分量对自适应有源噪声抵消系统性能影响很大。本文对参考信号中信号分量对AANC系统性能的影响进行了详细的分析,得到自适应滤波器解无约束的条件下,AANC系统输出端信噪比、信号失真度及噪声分量功率谱的计算式,并通过引入模平方相干函数提出衡量AANC系统处理增益的评估方法。
线谱噪声主要集中在自噪声的低频段。本文提出了一种采用切比雪夫多项式的直接并联型结构线谱噪声多通道有源陷波器,并且与直接型结构和并联型结构有源抵消器进行了比较。采用切比雪夫多项式在一定程度上保证了可靠的参考输入,采用直接并联型结构增大了参考输入中各谐波分量之间的频率间隔,提高了收敛速度。同时,本文提出了一种采用单位脉冲串的多通道自适应有源噪声抵消器,将这种有源噪声抵消器和Delayed-X LMS算法相结合,可以大大的减小运算量,并且也可以保证良好的收敛特性。
连续谱噪声属于宽带噪声。本文首先介绍了时域多通道滤波—X最小二乘(MFXRLS)算法,然后重点提出了一种基于线性卷积的频域多通道滤波—X最小二乘(MLFFXRLS)算法。通过理论分析和计算机仿真可以看出,MLFFXRLS
Submarine noise is the main interference of passive sonar system, which decreases the SNR at the input of the passive sonar, resulting in the deduction of sonar ranging. Therefore, reduction of submarine noise is of great importance. The reduction of submarine noise is a systematic project, requiring enormous financial support as well as series of techniques which have not yet been resolved fundamentally up till now so that researches on the techniques of adaptive active submarine noise canceling is meaningful and valuable for practical application. Applying the acoustical principles, our research subject is to find out a new adaptive active noise canceling technique, which will retain the signal energy during the noise canceling process. This technique is creative and much more difficult compared with conventional active adaptive noise canceling.AANC(Adaptive Active Noise Cancellation) works on the principle of destructive interference between the sound fields generated by the original "primary" sound source and that due to other "secondary" sources, whose acoustic outputs can be controlled by controllers, which are usually adaptive filters. The key is the configuration of adaptive filters and the corresponding algorithm in AANC systems.It's great for the effect of the signal components in the reference input on the performance of the AANC systems. In this paper, the effect of the signal components combined with the reference noises on the performance of the AANC systems has been studied comprehensively. Mathematical expressions of the signal-to-noise density ratio, signal distortion and noise power spectrum at the adaptive active noise canceller output have been derived under the condition of no constraints for the adaptive solution. By introducing Modular Squared Coherence(MSC) function to the AANC systems, the method for evaluating the processing gain of the AANC systems is proposed in the paper.
The line noise is a primary low frequency component of self-noise in submarines. In this paper, a hybrid active periodic noise canceller based on Chebyshev Polynomials has been introduced, and it has been compared with the direct form and the parallel form. Using chebyshev polynomials assures reliable reference inputs to a certain extent. The frequency difference between any two successive sinusoidal components is effectively increased in the hybrid form, as compared to the direct implementation technique. The rate of convergence of each adaptive filter can be significantly improved. In this paper, an AANC using a pulse train has been introduced to reduce the line interference. It has been shown that the total computational cost decreases if the AANC is combined with the Delayed-X LMS algorithm, and the excellent convergence performance has been obtained.The continuous power spectrum noise is wideband noise. First, the multi-channel filtered-x recursive-least-squares(MFXRLS) algorithms are introduced in time domain in this paper. Secondly, the frequency domain multi-channel filtered-X recursive least squares based on linear convolution(MLFFXRLS) algorithm has been proposed. It can be seen from the theoretical analysis and computer simulations that the MLFFXRLS algorithm will be have a much lower computational load than the MFXRLS algorithm, and the MLFFXRLS algorithm will be have a lower computational load than the MFXLMS algorithm for large channels numbers. In this paper, a delayless subband multi-channel system for active broadband self-noise canceling is also introduced, which has computational and convergence speed advantages comparable to a conventional subband design but without introducing any delay in the cancellation path.Finally, we analyze the real data using the proposed algorithms in the paper. In the case of uncorrelated signal and noise, whose bandwidths are both 2kHz, it can be shown from the processing that the adaptive processing gain of 21 dB was obtained, applying the MLFFXRLS algorithm, under the conditions of 2 control actuators, 2 error sensors and the perfect transfer functions of the primary paths and secondary paths to a certain extent if SNR
is lower than -45dB in the reference input. The results validate the effectiveness of the proposed algorithms in the practice.
引文
[1] [美]R.J.尤立克著.洪申译.水声原理.第三版.哈尔滨:哈尔滨船舶工程学院出版社,1990:279-280页
[2] 刘伯胜,雷家煜主编.水声学原理.哈尔滨:哈尔滨工程大学出版社,1997:236页
[3] S. J. ELLIOTT AND P. A. NELSON. Active noise control. IEEE signal processing magazine. October 1993: 12-35P
[4] 陈克安著.有源噪声控制.北京:国防工业出版社,2003:8-15页,112-114页
[5] Eghtesadi K. Active attenuation of noise——the monopole system. Journal of the Acoustical Society of America, 1982: 608-611P
[6] 沙家正.管道有源消声器.声学学报7(2),1982:137-147页
[7] Swinbanks M A. The active control of sound propagation in long ducts. Journal of Sound and Vibration, 1973: 411-436P
[8] Nelson P A, Elliott S J. Active control of sound, Academic Press, London, 1992
[9] Fuller C R, Hansen C H, Snyder S D. Active control of sound radiation from a vibrating rectangular panel by sound sources and vibration inputs: an experimental comparison. Journal of Sound and Vibration, 1991: 195-215P
[10] Ross C F. An algorithm for designing a broadband active sound control system. Journal of Sound and Vibration, 1982, 80(3): 373-380P
[11] Ross C F. An adaptive digital filter for a broadband active sound control system. Journal of Sound and Vibration, 1982, 80(3): 381-388P
[12] Roure A. Self-adaptive broadband active sound control system. Journal of Sound and Vibration, 1985, 101(3): 429-441P
[13] B. Widrow et al. Adaptive noise cancelling: Principles and applications. Proc. IEEE, 1975, 63(12), 1692-1716P
[14] Burgress J C. Active adaptive sound control in a duct: a computer simulation. Journal of the Acoustical Society of America. 1981, 70(3): 715-726P
[15] Hansen C H. Active noise control: from laboratory to industrial implementation. Proceedings of Noise Control. State College, Pennsylvania. 1997: 3-39P
[16] H. F. Olson, E. G. May. Electronic Sound Absorber. JASA, 1953: 1130—1136P
[17] H. F. Olson. Electronic Control of Noise. Vibration and Reverberation, JASA, 1956, 28(5): 966-972P
[18] 朱彦武,连小珉,蒋孝煜等.复合式新型有源消声耳罩.中国专利第94204976.4号
[19] 朱彦武.有源消声耳罩的研究.清华大学博士学位论文.1995:2-10页
[20] 蒋国健,任克明,马杰等.噪声抵消法估计和抑制声纳部位主要自噪声,声学学报.1996,21 (4):289-296页
[21] 俞孟萨,叶剑平等.船舶声纳部位自噪声的预报方法及其控制技术,船舶力学,6 (5),2002年,80-94页
[22] 陈克安,马远良著.自适应有源噪声控制——原理、算法及实现.西北工业大学出版社.1993:280页
[23] 德国发明以噪降噪的“安静岛”系统.科技日报.2002年03月22日
[24] D. H. Crawford and R. W. Stewart, E. Toma. A Novel Adaptive IIR Filter for Active Noise Control. Proceeding of the IEEE, 1996: 1629—1632P
[25] Scott D. Snyder. Active Control Using IIR Filters-A Second Look. Proceeding of the IEEE, 1994: 241-244P
[26] Jong Boo Kim, Tae Pyo Lee, Kook Hyun Yim. Feedforward IIR Active Noise Control Using Genetic Algorithm. Proceeding of the IEEE, 1999: 436-441P
[27] Carlos Mosquera, Jose A, Gdmez and Fernando Perez-Gonzalez. Filtered Error Adaptive Algorithms and Their Application to Active Noise Control. Proceeding of the IEEE, 1998: 1701-1704P
[28] Kook Hyun Yim, Jong Boo Kim, Tae Pyo Lee, Doo Soo Ahn. Genetic Adaptive IIR Filtering Algorithm for Active Noise Control. Proceedings of IEEE International Fuzzy Systems Conference, 1999: 1723-1728P
[29] Martin Bouchard. Numerically stable fast convergence least-squares algorithms for multichannel active sound cancellation systems and sound deconvolution systems. Signal Processing, 2002:721-736P
[30] Martin Bouchard, and Stephan Quednau. Multichannel Recursive-Least-Squares Algorithms and Fast-Transversal-Filter Algorithm for Active Noise Control and Sound Reproduction Systems. IEEE Trans. Acoustics, Speech and Signal Processing,2000,8(5): 606-618P
[31] Young C. Park & Scott D. Sommerfeldt. A Fast Adaptive Noise Control Algorithm Based on the Lattice Structure. Applied Acoustics, 1996, 47: 1-25P
[32] Kensaku Fujii, Juro Ohga. Method to update the coefficients of the secondary path filter under active noise control. Signal Processing, 2001, 81: 381-387P
[33] X.Qiu and C.H.Hansen. An Algorithm for Active Control of Transformer noise with on-line Cancellation Path Modelling Based on the Perturbation Method. Journal of Sound and Vibration, 2001, 240(4): 647-665P
[34] Alberto Gonzalez, Jose J.Lopez. Time Domain Recursive Deconvolution in Sound Reproduction.IEEE,2000:833-835P
[35] H.-S. Kim and Y.Park. Delayed-X LMS Algorithm: An Efficient ANC Algorithm Utilizing Robustness of Cancellation Path Model. Journal of Sound and Vibration( 1998) 212(5): 875-887P
[36] D.C.Swanson, S.M.Hirsch, K.M.Reichard, J.Tichy. Development of a frequency-domain filtered-x intensity ANC algorithm. Applied Acoustics, 1999:39-49P
[37] Cheng-Yuan Chang and Kuo-Kai Shyu. A self-tuning fuzzy filtered-U algorithm with the application of active noise control. The 27th Annual Conference of the IEEE Industrial Electronics Society, 2001:474-478P
[38] Sven Johansson,Sven Nordebo, and Ingvar Claesson. Convergence
Analysis of a Twin-Reference Complex Least-Mean-Squares Algorithm. IEEE Trans. on Speech andAudio Processing, 2002: 213-221P
[39] A. Kuo Wang, Wei Ren. Convergence analysis of the filtered-U algorithm for active noise control. Signal Processing, 1999, 73: 255-266P
[40] Martin Bouchard. Inverse Structure for Active Noise Control and Combined Active Noise Control/Sound Reproduction Systems. IEEE Trans. Speech and Audio Processing, 2001, 9(2): 141-151P
[41] Masato Miyoshi and Yutaka Kaneda. Inverse Filtering of Room Acoustics. IEEE Trans. on Acoustics, Speech, and Signal Processing, 1988, 36(2): 145-152P
[42] Jun-il Sohn, Minho Lee. Selective attention system using new active noise controller. Neurocomputing, 2000:197-204P
[43] Martin bouchard. New Recursive-Least-Squares Algorithms for Nonlinear Active Control of Sound and Vibration Using Neural Networks. IEEE Trans. on Neural Networks, 2001, 12(1): 135-147P
[44] Martin bouchard, Bruno Paillard and Chon Tan Le Dinh. Improved Training of Neural Networks for the Nonlinear Active Control of Sound and Vibration. IEEE Trans. on Neural Networks, 1999, 10(2): 391-401P
[45] Li Tan, Jean Jiang. Adaptive Volterra Filters for Active Control of Nonlinear Noise Processes. IEEE Trans. on Signal Processing, 2001, 49(8): 1667-1676P
[46] 张玉璘,陈伟民,杨建春,黄尚廉.小波变换自适应滤波器及其在主动噪声控制中的应用,控制与决策.2002,17(1):107-110P
[47] 张菊香,邱阳.利用多层感知神经网络对空调噪声的控制研究.机械科学与技术.2001,20(2):257-259P
[48] 陈克安,孙进才.局部空间自适应宽带有源消声.应用声学,1991,No.4:26-30P
[49] 孙旭,陈端石.次级通道模型误差下滤波X型最小均方差算法收敛性分析.声学学报,2002,27(2):97-101页
[50] 孙旭,陈端石.次级通道模型误差下滤波X型最小均方差算法性能的 分析.声学学报,2003,28(1):73-78页
[51] S. J. Elliott, P. A. Nelson. Multichannel Active Sound Control Using Adaptive Filtering. Proceedings of IEEE, 1988: 2590-2593P
[52] Jie Gu and Sze Fong Yau. A Moder-Based Approach To Active Noise Cancellation Using Loudspeaker Array. Proceedings of IEEE, 1997: 379-382P
[53] Martin Bouchard, Scott Norcross. Computational load reduction of fast convergence algorithms for multichannel active control. Signal Processing, 2003:121-134P
[54] Carlos Mosquera, Fernando Perez-Gonzalez. Convergence analysis of the multiple-channel filtered-U recursive LMS algorithm for active noise control. SignalProcessing , 2000:849-856P
[55] Fan Jiang, Masahiro Bunya, Hiromitsu Ohmori, Akira Sano. New Robust Adaptive Algorithm for Multichannel Adaptive Active Noise Control. Proceedings of the IEEE International Conference on Control Applications, 1997: 528-533P
[56] STEPHEN J. ELLIOTT. A Multiple Error LMS Algorithm and Its Application to the Active Control of Sound and Vibration. IEEE Trans. ASSP, 1987, 35(10): 1423-1434P
[57] M. DE Diego and Gonzalez. Perfomance Evaluation of Multichannel Adaptive Algorithms for Local Active Noise Control. Journal of Sound and Vibration, 2001, 244(4): 615-634P
[58] Martin Bouchard. Multichannel Affine and Fast Affine Projection Algorithms for Active Noise Control and Acoustic Equalization Systems. IEEE Trans. Speech and Audio Processing, 2003, 11(1): 54-60P
[59] 田静.三维空间有源噪声控制系统研究.中国科学院声学研究所博士论文.1991:1—10页
[60] 沙家正,孙广荣,曹水轩,吴启学.有源消声的机理研究.声学学报,1983,8(2):93-99页
[61] 田静.关于单极子次级声源管道降噪能量机制的理论分析.声学学报, 1992, 17(5): 369-374页
[62] Synder S D, Hansen C H. Active noise control in duct: some physical insights. Journal of the Acoustical of America, 1989, 86: 184-194P
[63] Elliott S J, Nelson P A, Johnson M E. Power output minimization and power absorption in the active control of sound. Journal of the Acoustical Society of America, 1993, 94: 185-195P
[64] M. Bouchard. An Alternative Feedback Structure for the Adaptive Active Control. of Periodic and Time-varying Periodic. Disturbances. Journal of Sound and Vibration, 1998, 210(4): 517-527P
[65] T. F. Haddad, M. A. Khasanech. A new forced LMS-based adaptive algorithm utilizing the principle of potential energy. Journal of the Franklin Institue, 2000, 337: 515-542P
[66] G. Chen and T. Sone. The Stability and Convergence Characterstics of the Delayd-X LMS Algorithm in ANC Systems. Journal of Sound and Vibration, 1998, 216(4): 637-648P
[67] Fan Jiang,, Hiroyuki Tsuji, Hiromitsu Ohmori, and Akira Sano. Adaptation for Active Noise Control. IEEE Control Systems, 1997: 36-47P
[68] 朱华,黄辉宁,李永庆,梅文博编.随机信号分析.北京理工大学出版社,1995:136—156页,190-200页,257-262页
[69] 连兵.相关噪声抵消系统的研究.大连理工大学博士论文.1998:19—21页
[70] B.维德罗著,王永德译.自适应信号处理.四川大学出版社,1991:238-241页
[71] [美]Simon Haykin著.自适应滤波器原理.第三版 北京:电子工业出版社,1999:50-59页
[72] Vijay Parsa, Philip A. Parker, Robert N, Scott. Performance Analysis of a Crosstalk Resistant Adaptive Noise Canceller. IEEE Trans. Circuits and Systems-Ⅱ: Analog and Digital Signal Processing, 1996, 43(7): 473-482P
[73] Vijay Parsa, Philip A. Parker, Robert Scott. Crosstalk Resistant Adaptive Noise Cancellation Applied to Somatosensory Evoked Potential Enhancement. Proceedings of IEEE, 1995: 2931-2934P
[74] V. Parsa and P. Parker. Constrained Crosstalk Resistant Adaptive Noise Canceller. Electronics Letters, 1994, 30(16): 1276-1277P
[75] Carlos R. Martins and Moises S. Piedade. New Adaptive Structures for Speech Enhancement in Noisy Environments. Proceedings of IEEE, 1999: 241-244P
[76] Sen M. Kuo, Wei M. Peng. Principle and Applications of Asymmetric Crosstalk-Resistant Adaptive Noise Canceller. Journal of the Franklin Institute, 2000, 37, 57-71P
[77] Sen M. Kuo and Dennis R. Morgan. Active Noise Control: A Tutorial Review. Proceedings of the IEEE, 1999, 87(6):943-973P
[78] Dennis R. Morgan and Charles Sanford. A Control Theory Approach to the Stability and Transient Analysis of the Filtered-X LMS Adaptive Notch Filter. IEEE Trans. Signal Processing, 1992, 40(9): 2341-2346P
[79] Lisa A. Sievers and Andreas H. von Flotow. Comparison and Extensions of Control Methods for Narrow-Band Disturbance Rejection. IEEE Trans. Signal Processing, 1992, 40(10): 2377-2389P
[80] Laszlo Sujbert, Gabor Peceli. Signal model based periodic noise controller design. Measurement, 1997, 20(2): 135-141P
[81] Marc Bodson, Jonathan S. Jensen, and Scott C. Douglas. Active Noise Control for Periodic Disturbances. IEEE Trans. Control Systems Technology, 2001, 9(1): 200-205P
[82] Neil J. Bershad, and Jose Carlos M. Bermudez. Sinusoidal Interference Rejection Analysis of an LMS Adaptive Feedforward Controller with a Noisy Periodic Reference. IEEE Trans. Signal Processing, 1992, 46(5): 1298-1312P
[83] John R. Glover, JR.. Adaptive Noise Canceling Applied to Sinusoidal Interferences. IEEE Trans. Acoustics, Speech, and Signal Processing, 1977, 25(6): 484-491P
[84] 江峰,惠俊英,蔡平等.谐波线谱簇干扰自适应抵消器.声学学报, 2000,25(1):21-26页
[85] 江峰,惠俊英,蔡平等.自适应线谱干扰抵消器的理论分析及其极窄带实现.哈尔滨工程大学学报.1998,19(5):42-48页
[86] 王竹溪,郭敦仁著.特殊函数概论.北京:北京大学出版社,2000:168-173页
[87] Hidefumi KOBATAKE. A Synchronous Adaptive Noise Canceller for Periodic Interference. Proc. ICASSP, 1982, 1424-1427P
[88] S. J. Elliott and P. Darlington. Adaptive Cancellation of Periodic, Synchronously Sampled Interference. IEEE Trans. Acoustics, Speech and Signal Processing, 1985, 33 (3): 715-717P
[89] Sen M. Kuo, Mansour Tahernezhadi, and Li Ji. Frequency-Domain Periodic Active Noise Control and Equalization. IEEE Trans. Speech and Audio Processing, 1997, 5(4): 348-356P
[90] Bernhard H. Nitsch. A frequency-selective stepfactor control for an adaptive filter algorithm working in the frequency domain. Signal Processing, 2000, 80:1733-1745P
[91] Martin Bouchard and Bruno Paillard. A transform domain optimization to increase the convergence speed of the multichannel filtered-X least-mean-square algorithm. J. Acoust. Soc. Am, 1996, 100(5): 3203-3214P
[92] Song Liu, Xiaodong Li, Jing Tian. Transform domain adaptive filter in active noise control. Proceedings of ICSP, 2002: 272-275P
[93] D. R. Morgan and J. Thi. A Delayless subband adaptive filter. IEEE Trans. Signal Processing, 1995, 8: 1819-1830P
[94] James Thi, and Dennis R. Morgan. Delayless Subband Active Noise Control. Proceeding of IEEE, 1993:181-184P
[95] Jeong-Hyeon Yun, Young-Cheol Park, Dae-Hee Youn. An Active Noise Control Algorithm with on-line System Identification Based on A Delayless Subband Adaptive Filter Architecture. Proceeding of IEEE, 1997:1370-1373P
[96] Seon Joon Park, Jeong Hyeon Yun, Young Cheol Park, and Dae Hee Youn. A Delayless Subband Active Noise Control System for Wideband Noise Control. IEEE Trans. Speech and Audio Processing, 2001,9(8):892-899P
[97] J. Poshtan, F. Taringoo, A. Nasiri, M. H. Kahaie. Multichannel Active Noise Control Algorithm Using Align Matrix. Proceeding of IEEE, 2003: 435-438P
[98] Mariane R. Petraglia, Rogerio G. Alves, M. N. S. Swamy. A New Open Loop Delayless Subband Adaptive Filter Structure. Proceeding of IEEE, 2002:1345-1348P
[2] 刘伯胜,雷家煜主编.水声学原理.哈尔滨:哈尔滨工程大学出版社,1997:236页
[3] S. J. ELLIOTT AND P. A. NELSON. Active noise control. IEEE signal processing magazine. October 1993: 12-35P
[4] 陈克安著.有源噪声控制.北京:国防工业出版社,2003:8-15页,112-114页
[5] Eghtesadi K. Active attenuation of noise——the monopole system. Journal of the Acoustical Society of America, 1982: 608-611P
[6] 沙家正.管道有源消声器.声学学报7(2),1982:137-147页
[7] Swinbanks M A. The active control of sound propagation in long ducts. Journal of Sound and Vibration, 1973: 411-436P
[8] Nelson P A, Elliott S J. Active control of sound, Academic Press, London, 1992
[9] Fuller C R, Hansen C H, Snyder S D. Active control of sound radiation from a vibrating rectangular panel by sound sources and vibration inputs: an experimental comparison. Journal of Sound and Vibration, 1991: 195-215P
[10] Ross C F. An algorithm for designing a broadband active sound control system. Journal of Sound and Vibration, 1982, 80(3): 373-380P
[11] Ross C F. An adaptive digital filter for a broadband active sound control system. Journal of Sound and Vibration, 1982, 80(3): 381-388P
[12] Roure A. Self-adaptive broadband active sound control system. Journal of Sound and Vibration, 1985, 101(3): 429-441P
[13] B. Widrow et al. Adaptive noise cancelling: Principles and applications. Proc. IEEE, 1975, 63(12), 1692-1716P
[14] Burgress J C. Active adaptive sound control in a duct: a computer simulation. Journal of the Acoustical Society of America. 1981, 70(3): 715-726P
[15] Hansen C H. Active noise control: from laboratory to industrial implementation. Proceedings of Noise Control. State College, Pennsylvania. 1997: 3-39P
[16] H. F. Olson, E. G. May. Electronic Sound Absorber. JASA, 1953: 1130—1136P
[17] H. F. Olson. Electronic Control of Noise. Vibration and Reverberation, JASA, 1956, 28(5): 966-972P
[18] 朱彦武,连小珉,蒋孝煜等.复合式新型有源消声耳罩.中国专利第94204976.4号
[19] 朱彦武.有源消声耳罩的研究.清华大学博士学位论文.1995:2-10页
[20] 蒋国健,任克明,马杰等.噪声抵消法估计和抑制声纳部位主要自噪声,声学学报.1996,21 (4):289-296页
[21] 俞孟萨,叶剑平等.船舶声纳部位自噪声的预报方法及其控制技术,船舶力学,6 (5),2002年,80-94页
[22] 陈克安,马远良著.自适应有源噪声控制——原理、算法及实现.西北工业大学出版社.1993:280页
[23] 德国发明以噪降噪的“安静岛”系统.科技日报.2002年03月22日
[24] D. H. Crawford and R. W. Stewart, E. Toma. A Novel Adaptive IIR Filter for Active Noise Control. Proceeding of the IEEE, 1996: 1629—1632P
[25] Scott D. Snyder. Active Control Using IIR Filters-A Second Look. Proceeding of the IEEE, 1994: 241-244P
[26] Jong Boo Kim, Tae Pyo Lee, Kook Hyun Yim. Feedforward IIR Active Noise Control Using Genetic Algorithm. Proceeding of the IEEE, 1999: 436-441P
[27] Carlos Mosquera, Jose A, Gdmez and Fernando Perez-Gonzalez. Filtered Error Adaptive Algorithms and Their Application to Active Noise Control. Proceeding of the IEEE, 1998: 1701-1704P
[28] Kook Hyun Yim, Jong Boo Kim, Tae Pyo Lee, Doo Soo Ahn. Genetic Adaptive IIR Filtering Algorithm for Active Noise Control. Proceedings of IEEE International Fuzzy Systems Conference, 1999: 1723-1728P
[29] Martin Bouchard. Numerically stable fast convergence least-squares algorithms for multichannel active sound cancellation systems and sound deconvolution systems. Signal Processing, 2002:721-736P
[30] Martin Bouchard, and Stephan Quednau. Multichannel Recursive-Least-Squares Algorithms and Fast-Transversal-Filter Algorithm for Active Noise Control and Sound Reproduction Systems. IEEE Trans. Acoustics, Speech and Signal Processing,2000,8(5): 606-618P
[31] Young C. Park & Scott D. Sommerfeldt. A Fast Adaptive Noise Control Algorithm Based on the Lattice Structure. Applied Acoustics, 1996, 47: 1-25P
[32] Kensaku Fujii, Juro Ohga. Method to update the coefficients of the secondary path filter under active noise control. Signal Processing, 2001, 81: 381-387P
[33] X.Qiu and C.H.Hansen. An Algorithm for Active Control of Transformer noise with on-line Cancellation Path Modelling Based on the Perturbation Method. Journal of Sound and Vibration, 2001, 240(4): 647-665P
[34] Alberto Gonzalez, Jose J.Lopez. Time Domain Recursive Deconvolution in Sound Reproduction.IEEE,2000:833-835P
[35] H.-S. Kim and Y.Park. Delayed-X LMS Algorithm: An Efficient ANC Algorithm Utilizing Robustness of Cancellation Path Model. Journal of Sound and Vibration( 1998) 212(5): 875-887P
[36] D.C.Swanson, S.M.Hirsch, K.M.Reichard, J.Tichy. Development of a frequency-domain filtered-x intensity ANC algorithm. Applied Acoustics, 1999:39-49P
[37] Cheng-Yuan Chang and Kuo-Kai Shyu. A self-tuning fuzzy filtered-U algorithm with the application of active noise control. The 27th Annual Conference of the IEEE Industrial Electronics Society, 2001:474-478P
[38] Sven Johansson,Sven Nordebo, and Ingvar Claesson. Convergence
Analysis of a Twin-Reference Complex Least-Mean-Squares Algorithm. IEEE Trans. on Speech andAudio Processing, 2002: 213-221P
[39] A. Kuo Wang, Wei Ren. Convergence analysis of the filtered-U algorithm for active noise control. Signal Processing, 1999, 73: 255-266P
[40] Martin Bouchard. Inverse Structure for Active Noise Control and Combined Active Noise Control/Sound Reproduction Systems. IEEE Trans. Speech and Audio Processing, 2001, 9(2): 141-151P
[41] Masato Miyoshi and Yutaka Kaneda. Inverse Filtering of Room Acoustics. IEEE Trans. on Acoustics, Speech, and Signal Processing, 1988, 36(2): 145-152P
[42] Jun-il Sohn, Minho Lee. Selective attention system using new active noise controller. Neurocomputing, 2000:197-204P
[43] Martin bouchard. New Recursive-Least-Squares Algorithms for Nonlinear Active Control of Sound and Vibration Using Neural Networks. IEEE Trans. on Neural Networks, 2001, 12(1): 135-147P
[44] Martin bouchard, Bruno Paillard and Chon Tan Le Dinh. Improved Training of Neural Networks for the Nonlinear Active Control of Sound and Vibration. IEEE Trans. on Neural Networks, 1999, 10(2): 391-401P
[45] Li Tan, Jean Jiang. Adaptive Volterra Filters for Active Control of Nonlinear Noise Processes. IEEE Trans. on Signal Processing, 2001, 49(8): 1667-1676P
[46] 张玉璘,陈伟民,杨建春,黄尚廉.小波变换自适应滤波器及其在主动噪声控制中的应用,控制与决策.2002,17(1):107-110P
[47] 张菊香,邱阳.利用多层感知神经网络对空调噪声的控制研究.机械科学与技术.2001,20(2):257-259P
[48] 陈克安,孙进才.局部空间自适应宽带有源消声.应用声学,1991,No.4:26-30P
[49] 孙旭,陈端石.次级通道模型误差下滤波X型最小均方差算法收敛性分析.声学学报,2002,27(2):97-101页
[50] 孙旭,陈端石.次级通道模型误差下滤波X型最小均方差算法性能的 分析.声学学报,2003,28(1):73-78页
[51] S. J. Elliott, P. A. Nelson. Multichannel Active Sound Control Using Adaptive Filtering. Proceedings of IEEE, 1988: 2590-2593P
[52] Jie Gu and Sze Fong Yau. A Moder-Based Approach To Active Noise Cancellation Using Loudspeaker Array. Proceedings of IEEE, 1997: 379-382P
[53] Martin Bouchard, Scott Norcross. Computational load reduction of fast convergence algorithms for multichannel active control. Signal Processing, 2003:121-134P
[54] Carlos Mosquera, Fernando Perez-Gonzalez. Convergence analysis of the multiple-channel filtered-U recursive LMS algorithm for active noise control. SignalProcessing , 2000:849-856P
[55] Fan Jiang, Masahiro Bunya, Hiromitsu Ohmori, Akira Sano. New Robust Adaptive Algorithm for Multichannel Adaptive Active Noise Control. Proceedings of the IEEE International Conference on Control Applications, 1997: 528-533P
[56] STEPHEN J. ELLIOTT. A Multiple Error LMS Algorithm and Its Application to the Active Control of Sound and Vibration. IEEE Trans. ASSP, 1987, 35(10): 1423-1434P
[57] M. DE Diego and Gonzalez. Perfomance Evaluation of Multichannel Adaptive Algorithms for Local Active Noise Control. Journal of Sound and Vibration, 2001, 244(4): 615-634P
[58] Martin Bouchard. Multichannel Affine and Fast Affine Projection Algorithms for Active Noise Control and Acoustic Equalization Systems. IEEE Trans. Speech and Audio Processing, 2003, 11(1): 54-60P
[59] 田静.三维空间有源噪声控制系统研究.中国科学院声学研究所博士论文.1991:1—10页
[60] 沙家正,孙广荣,曹水轩,吴启学.有源消声的机理研究.声学学报,1983,8(2):93-99页
[61] 田静.关于单极子次级声源管道降噪能量机制的理论分析.声学学报, 1992, 17(5): 369-374页
[62] Synder S D, Hansen C H. Active noise control in duct: some physical insights. Journal of the Acoustical of America, 1989, 86: 184-194P
[63] Elliott S J, Nelson P A, Johnson M E. Power output minimization and power absorption in the active control of sound. Journal of the Acoustical Society of America, 1993, 94: 185-195P
[64] M. Bouchard. An Alternative Feedback Structure for the Adaptive Active Control. of Periodic and Time-varying Periodic. Disturbances. Journal of Sound and Vibration, 1998, 210(4): 517-527P
[65] T. F. Haddad, M. A. Khasanech. A new forced LMS-based adaptive algorithm utilizing the principle of potential energy. Journal of the Franklin Institue, 2000, 337: 515-542P
[66] G. Chen and T. Sone. The Stability and Convergence Characterstics of the Delayd-X LMS Algorithm in ANC Systems. Journal of Sound and Vibration, 1998, 216(4): 637-648P
[67] Fan Jiang,, Hiroyuki Tsuji, Hiromitsu Ohmori, and Akira Sano. Adaptation for Active Noise Control. IEEE Control Systems, 1997: 36-47P
[68] 朱华,黄辉宁,李永庆,梅文博编.随机信号分析.北京理工大学出版社,1995:136—156页,190-200页,257-262页
[69] 连兵.相关噪声抵消系统的研究.大连理工大学博士论文.1998:19—21页
[70] B.维德罗著,王永德译.自适应信号处理.四川大学出版社,1991:238-241页
[71] [美]Simon Haykin著.自适应滤波器原理.第三版 北京:电子工业出版社,1999:50-59页
[72] Vijay Parsa, Philip A. Parker, Robert N, Scott. Performance Analysis of a Crosstalk Resistant Adaptive Noise Canceller. IEEE Trans. Circuits and Systems-Ⅱ: Analog and Digital Signal Processing, 1996, 43(7): 473-482P
[73] Vijay Parsa, Philip A. Parker, Robert Scott. Crosstalk Resistant Adaptive Noise Cancellation Applied to Somatosensory Evoked Potential Enhancement. Proceedings of IEEE, 1995: 2931-2934P
[74] V. Parsa and P. Parker. Constrained Crosstalk Resistant Adaptive Noise Canceller. Electronics Letters, 1994, 30(16): 1276-1277P
[75] Carlos R. Martins and Moises S. Piedade. New Adaptive Structures for Speech Enhancement in Noisy Environments. Proceedings of IEEE, 1999: 241-244P
[76] Sen M. Kuo, Wei M. Peng. Principle and Applications of Asymmetric Crosstalk-Resistant Adaptive Noise Canceller. Journal of the Franklin Institute, 2000, 37, 57-71P
[77] Sen M. Kuo and Dennis R. Morgan. Active Noise Control: A Tutorial Review. Proceedings of the IEEE, 1999, 87(6):943-973P
[78] Dennis R. Morgan and Charles Sanford. A Control Theory Approach to the Stability and Transient Analysis of the Filtered-X LMS Adaptive Notch Filter. IEEE Trans. Signal Processing, 1992, 40(9): 2341-2346P
[79] Lisa A. Sievers and Andreas H. von Flotow. Comparison and Extensions of Control Methods for Narrow-Band Disturbance Rejection. IEEE Trans. Signal Processing, 1992, 40(10): 2377-2389P
[80] Laszlo Sujbert, Gabor Peceli. Signal model based periodic noise controller design. Measurement, 1997, 20(2): 135-141P
[81] Marc Bodson, Jonathan S. Jensen, and Scott C. Douglas. Active Noise Control for Periodic Disturbances. IEEE Trans. Control Systems Technology, 2001, 9(1): 200-205P
[82] Neil J. Bershad, and Jose Carlos M. Bermudez. Sinusoidal Interference Rejection Analysis of an LMS Adaptive Feedforward Controller with a Noisy Periodic Reference. IEEE Trans. Signal Processing, 1992, 46(5): 1298-1312P
[83] John R. Glover, JR.. Adaptive Noise Canceling Applied to Sinusoidal Interferences. IEEE Trans. Acoustics, Speech, and Signal Processing, 1977, 25(6): 484-491P
[84] 江峰,惠俊英,蔡平等.谐波线谱簇干扰自适应抵消器.声学学报, 2000,25(1):21-26页
[85] 江峰,惠俊英,蔡平等.自适应线谱干扰抵消器的理论分析及其极窄带实现.哈尔滨工程大学学报.1998,19(5):42-48页
[86] 王竹溪,郭敦仁著.特殊函数概论.北京:北京大学出版社,2000:168-173页
[87] Hidefumi KOBATAKE. A Synchronous Adaptive Noise Canceller for Periodic Interference. Proc. ICASSP, 1982, 1424-1427P
[88] S. J. Elliott and P. Darlington. Adaptive Cancellation of Periodic, Synchronously Sampled Interference. IEEE Trans. Acoustics, Speech and Signal Processing, 1985, 33 (3): 715-717P
[89] Sen M. Kuo, Mansour Tahernezhadi, and Li Ji. Frequency-Domain Periodic Active Noise Control and Equalization. IEEE Trans. Speech and Audio Processing, 1997, 5(4): 348-356P
[90] Bernhard H. Nitsch. A frequency-selective stepfactor control for an adaptive filter algorithm working in the frequency domain. Signal Processing, 2000, 80:1733-1745P
[91] Martin Bouchard and Bruno Paillard. A transform domain optimization to increase the convergence speed of the multichannel filtered-X least-mean-square algorithm. J. Acoust. Soc. Am, 1996, 100(5): 3203-3214P
[92] Song Liu, Xiaodong Li, Jing Tian. Transform domain adaptive filter in active noise control. Proceedings of ICSP, 2002: 272-275P
[93] D. R. Morgan and J. Thi. A Delayless subband adaptive filter. IEEE Trans. Signal Processing, 1995, 8: 1819-1830P
[94] James Thi, and Dennis R. Morgan. Delayless Subband Active Noise Control. Proceeding of IEEE, 1993:181-184P
[95] Jeong-Hyeon Yun, Young-Cheol Park, Dae-Hee Youn. An Active Noise Control Algorithm with on-line System Identification Based on A Delayless Subband Adaptive Filter Architecture. Proceeding of IEEE, 1997:1370-1373P
[96] Seon Joon Park, Jeong Hyeon Yun, Young Cheol Park, and Dae Hee Youn. A Delayless Subband Active Noise Control System for Wideband Noise Control. IEEE Trans. Speech and Audio Processing, 2001,9(8):892-899P
[97] J. Poshtan, F. Taringoo, A. Nasiri, M. H. Kahaie. Multichannel Active Noise Control Algorithm Using Align Matrix. Proceeding of IEEE, 2003: 435-438P
[98] Mariane R. Petraglia, Rogerio G. Alves, M. N. S. Swamy. A New Open Loop Delayless Subband Adaptive Filter Structure. Proceeding of IEEE, 2002:1345-1348P