Results 181 to 190 of about 1,530,208 (226)

The minimum mean squared error threshold

2001
This chapter investigates the mean squared error as a criterion for selecting an optimal soft threshold. In applications like image processing, it is often objected that this expression of the error does not always correspond to a more subjective experience of quality.
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On minimum mean square error speech enhancement

[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991
Motivation for using minimum mean square error (MMSE) estimation in noisy speech enhancement problems is given. An MMSE estimator which is based on hidden Markov modeling of the clean signal as well as the noise process is systematically developed. The MMSE estimator is tested and compared with the spectral subtraction estimator in vector quantization ...
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Minimum mean square error estimation in linear regression

Journal of Statistical Planning and Inference, 1993
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Liski, Erkki P., Toutenburg, Helge, Trenkler, Götz   +2 more
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Robust estimate with minimum mean squared error

Australian Surveyor, 1991
The result of any robust estimate depends on its weight function. But the weight function and its parameters are determined personally.
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Asymptotically minimum bit error rate block precoders for minimum mean square error equalization

Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2002, 2003
We determine linear block precoders which asymptotically minimize the bit error rate (BER) of block-based communication systems employing minimum mean square error (MMSE) equalization and threshold detection. The problem is solved by a two-stage optimization procedure in which a lower bound on the BER over its convex region is first minimized, followed
S.S. Chan, T.N. Davidson, K.M. Wong
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Linear Minimum Mean-Square Error Estimators Applied to Channel Equalization

IEEE Transactions on Communications, 1977
This concise paper investigates various aspects of the application of unbiased linear minimum mean-square error (ULMMSE) estimators to the equalization of channels used for digital data transmission. One application is to the equalization of the channel to a response free from intersymbol interference.
Cantoni, A., Butler, P.
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Moments and error expressions in polynomial minimum mean square estimatior

Information Sciences, 1976
The mathematical complexity of the minimum mean square estimators made inevitable the consideration of suboptimal solutions, such as the linear minimum mean square (m.m.s.) estimators. The compromise between performance and complexity can be, in general, less serious if the estimator that will substitute the optimum one is polynomial.
Kazakos, D., Papantoni-Kazakos, P.
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Speech enhancement using a minimum mean-square error log-spectral amplitude estimator

IEEE Transactions on Acoustics Speech and Signal Processing, 1984
Y. Ephraim, D. Malah
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Speech enhancement by combining spectral subtraction and minimum mean square error-spectrum power estimator based on zero crossing

International Journal of Speech Technology, 2018
G. ThimmarajaYadava, H. S. Jayanna
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Channel estimation for sparse channel OFDM systems using least square and minimum mean square error techniques

International Conference on Emerging Technologies, 2017
A. Farzamnia, Ngu War Hlaing, M. K. Haldar, Javad Rahebi   +3 more
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