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Volumn 95, Issue 6, 1994, Pages 3400-3408

Inverse filtering of a loudspeaker and room acoustics using time-delay neural networks

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTICS; FILTER; FOURIER TRANSFORMATION; MATHEMATICAL ANALYSIS; MODEL; NERVE CELL NETWORK; PRESSURE; PRIORITY JOURNAL; REVIEW; SIGNAL TRANSDUCTION; SIMULATION; SOUND;

EID: 0028362557     PISSN: 00014966     EISSN: NA     Source Type: Journal    
DOI: 10.1121/1.409959     Document Type: Article
Times cited : (19)

References (20)
  • 1
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    • Neely, S.T.1    Allen, J.B.2
  • 4
    • 0024769057 scopus 로고
    • Multiple point least squares equalization in a room using adaptive digital filters
    • S. J. Elliott and P. A. Nelson, “Multiple point least squares equalization in a room using adaptive digital filters,” J. Audio Eng. Soc. 37, 899–907 (1988).
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    • Elliott, S.J.1    Nelson, P.A.2
  • 5
    • 0020721882 scopus 로고
    • Electronic equalization of closed-box loudspeakers
    • R. L. Greiner and M. Schoessow, “Electronic equalization of closed-box loudspeakers,” J. Audio Eng. Soc. 31, 125–134 (1980).
    • (1980) J. Audio Eng. Soc. , vol.31 , pp. 125-134
    • Greiner, R.L.1    Schoessow, M.2
  • 7
    • 0023363499 scopus 로고
    • Modeling of the nonlinear response of electrodynamic louspeaker by a Volterra series expansion
    • A. J. M. Kaizer, “Modeling of the nonlinear response of electrodynamic louspeaker by a Volterra series expansion,” J. Audio Eng. Soc. 35, 421-433 (1987).
    • (1987) J. Audio Eng. Soc. , vol.35 , pp. 421-433
    • Kaizer, A.J.M.1
  • 8
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • K. Homik, M. Stinchcombe, and H. White, “Multilayer feedforward networks are universal approximators,” Neural Networks 2, 359–366 (1989).
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Homik, K.1    Stinchcombe, M.2    White, H.3
  • 9
    • 0024861871 scopus 로고
    • Approximations by superposition of a sigmoidal function
    • G. Cybenko, “Approximations by superposition of a sigmoidal function,” Math. Control Syst. Signals 2, 303–314 (1989).
    • (1989) Math. Control Syst. Signals , vol.2 , pp. 303-314
    • Cybenko, G.1
  • 10
    • 0025627940 scopus 로고
    • Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks
    • K. Homik, M. Stinchcombe, and H. White, “Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks,” Neural Networks 3, 551–560 (1990).
    • (1990) Neural Networks , vol.3 , pp. 551-560
    • Homik, K.1    Stinchcombe, M.2    White, H.3
  • 11
    • 0018455820 scopus 로고
    • Image method for efficiently simulating small-room acoustics
    • J. B. Allen and D. A. Berkley, “Image method for efficiently simulating small-room acoustics,” J. Acoust. Soc. Am. 65, 943–950 (1979).
    • (1979) J. Acoust. Soc. Am. , vol.65 , pp. 943-950
    • Allen, J.B.1    Berkley, D.A.2
  • 12
    • 0025636775 scopus 로고
    • The Stone-Weierstrass theorem and its applications to neural nets
    • M. E. Cotter, “The Stone-Weierstrass theorem and its applications to neural nets,” IEEE Trans. Neural Networks, 1, 290–295 (1990).
    • (1990) IEEE Trans. Neural Networks , vol.1 , pp. 290-295
    • Cotter, M.E.1
  • 14
    • 0025792215 scopus 로고
    • Bounds on the number of hidden neurons in multilayer perceptrons
    • S. C. Huang and Y. F. Huang, “Bounds on the number of hidden neurons in multilayer perceptrons,” IEEE Trans. Neural Networks, 2, 47–55 (1991).
    • (1991) IEEE Trans. Neural Networks , vol.2 , pp. 47-55
    • Huang, S.C.1    Huang, Y.F.2
  • 15
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • edited by D. E. Rumelhart and J. L. McCelland (M.I.T., Cambridge, MA
    • D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning internal representations by error propagation,” in Parallel Distributed Processing, edited by D. E. Rumelhart and J. L. McCelland (M.I.T., Cambridge, MA, 1986), pp. 318–362.
    • (1986) Parallel Distributed Processing , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 16
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    • Increased rates of convergence through learning rate adaptation
    • R. A. Jacobs, “Increased rates of convergence through learning rate adaptation,” Neural Networks, 295–307 (1988).
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  • 17
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    • Neural nets for adaptive filtering and adaptive pattern recognition
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    • Widrow, B.1    Winter, R.2
  • 20
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    • Correlation based model validity tests for non-linear models
    • S. A. Billings and W. S. F. Voon, “Correlation based model validity tests for non-linear models,” Int. J. Control 44, 235–244 (1986).
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    • Billings, S.A.1    Voon, W.S.F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.