Results 281 to 290 of about 530,731 (343)
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Sensor validation using minimum mean square error estimation
Mechanical Systems and Signal Processing, 2010Jyrki Kullaa
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Linear Minimum Mean Square Error Demosaicking
Single-Sensor Imaging, 2018D. Alleysson, Brice Chaix
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Minimum mean-square error quadrature
Journal of Statistical Computation and Simulation, 1993Minimum mean squared error linear estimators of the area under a curve are considered for cases when the observations are observed with error. The underlying functional form giving rise to the observations is left unspecified, leading to use of quadrature estimators for the true area.
Walter W. Piegorsch, A. John Bailer
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Unified ISAC Pareto Boundary Based on Mutual Information and Minimum Mean-Square Error Estimation
IEEE Transactions on CommunicationsThe performance of multiple-input multiple-output (MIMO) integrated sensing and communication systems (ISAC) can be evaluated from the perspectives of information theory and estimation theory to provide more fundamental insights.
Shuaijun Wang +5 more
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Estimation of the minimum mean square error of prediction
Biometrika, 1975SUMMARY Bloomfield (1973) and Jones (1964) have discussed the estimation of the error of prediction of a time series. Their results use the asymptotic normality of their estimates and we attempt to examine the validity of this approximation in the simplest case.
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Minimum mean-squared error covariance shaping
2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2004The paper develops and explores applications of a linear shaping transformation that minimizes the mean squared error (MSE) between the original and shaped data, i.e., that results in an output vector with the desired covariance that is as close as possible to the input, in an MSE sense.
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On minimum mean square error speech enhancement
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991Motivation 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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Fixed-width CSD multipliers with minimum mean square error
Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 2010Many multimedia and DSP applications require fixed-width multipliers, in which input data and output results have the same bit width. In this paper we investigate fixed-width multipliers where one of the input operand is a constant, encoded using canonic signed digit (CSD) representation.
Nicola Petra +6 more
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Moments and error expressions in polynomial minimum mean square estimatior
Information Sciences, 1976The 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.
Demetrios Kazakos, P. Papantoni-Kazakos
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Source imaging with minimum mean-squared error
The Journal of the Acoustical Society of America, 1993Prior knowledge of source size, shape, and radiation process, and of receiver noise correlations are incorporated in a linear minimum mean-squared error (MMSE) imaging estimator. Its resolution operator and expected squared estimation error are derived and are computed for discrete linear source and receive arrays.
Roland Stoughton, Stewart Strait
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