linear minimum mean-square error
Minimum Mean Square Error Single User Detection of SDMA Signals Transmitted over Nakagami Fading Channels
... The single-user detector considered is the linear minimum mean square error (MMSE) detector [9]. Furthermore, in con- trast to the popular Rayleigh fading channel model most of- ten ...
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Adaptive linear filtering design with minimum symbol error probability criterion
... the minimum mean square error (MMSE) principle [1,2] ...least mean square (LMS) algorithm, thus readily meet the real-time com- putational constraints of high-speed digital ...
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ICI cancellation using normalized minimum mean square error in MIMO OFDM systems
... Distributed Minimum Mean Square Error (DMMSE) algorithm [5] was proposed to achieve nearly optimal channel estimates at low complexity by makes use of the strong spatial correlation among ...
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A COMPARATIVE ANALYSIS OF MEAN SQUARE ERROR ADAPTIVE FILTER ALGORITHMS FOR GENERATION OF MODIFIED SCALING AND WAVELET FUNCTION
... uniform linear array with N isotropic elements, which forms the integral part of the FIR adaptive filter design is shown in ...on minimum squared error (MSE), therefore the spatial filtering problem ...
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Scalable kernel-based minimum mean square error estimate for light-field image compression
... locally linear embedding (LLE) is proposed in ...kernel-based minimum mean-square-error estimation prediction [15] and Gaussian process regression-based prediction method ...
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Adaptive minimum bit error rate filtering
... A linear filtering model is given in the general communication setting, and the theoretical MBER filtering solution is ...least mean square (LMS) ...
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Zero Forcing and Minimum Mean Square Error Multiuser Detection in Generalized Multicarrier DS CDMA Systems for Cognitive Radio
... the linear processing as in the single-user MF-based ...the error performance of the MC DS-CDMA using the SZF-MUD is much worse than that of the MC DS-CDMA using the ...
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The Minimum Error Minimax Probability Machine
... We construct a distribution-free Bayes optimal classifier called the Minimum Error Minimax Proba- bility Machine (MEMPM) in a worst-case setting, i.e., under all possible choices of class-conditional ...
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Application of Mean-Square Approximation for Piecewise Linear Optimal Compander Design for Gaussian Source and Gaussian Mixture Model
... proposed PLOC obtains higher signal quality (higher SQNR) in comparison to the uniform quantizer [2], [11]. In this particular case of comparison, the lowest obtained SQNR gain over the uniform quantizer is 0.7 dB and it ...
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Stabilizing Minimum Error Rate Training
... One possible approach to estimating log-linear weights on features is to dispense with the n-best lists employed by Och’s procedure and, instead, to optimize weights by directly accessing the de- coder. The ...
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Regularized Minimum Error Rate Training
... Optimization has traditionally relied on finding the direction of steepest ascent: the gradient. Unfortu- nately, the objective function optimized by MERT is piecewise constant; while it may admit a subgradi- ent, this ...
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Random non autonomous second order linear differential equations: mean square analytic solutions and their statistical properties
... els appearing in the area of mathematical physics like Airy, Hermite, Legendre, Laguerre and Bessel differential equations have been randomized and rigorously studied in [3, 4, 7, 8, 10], respectively. In these ...
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Bias and Mean Square Error of Reliability Estimators under the One and Two Random Effects Models: The Effect of Non Normality
... Firstly, the effect of non-normality of the scores distribution is not tangible for k > 25 (fairly large), where k is the number subjects. Secondly, large value of reliability, which is our main concern, has smaller ...
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Automatic Multiple Face Recognition and Annotation Based on Principle Component Analysis cum Least Mean Square Error (PLMSE)
... In this thesis work, we proposed a computational model of face detection and recognition and annotation, which is fast, reasonably simple, and accurate in constrained environments such as an office or a household. Face ...
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MD )are better than the others for all sample sizes with different percentages outlier. Index Terms —Mean absolute deviation, Mean square error, Robustness standard deviation, Monte Carlo simulation, Multiple linear regression, Residuals.
... measure based on the mean squared error (MSE) is not robust, since it may be highly influenced by events of small probability. This paper, author uses the median absolute deviation which is denoted MAD (see ...
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Least Mean Square (LMS) for Smart Antenna
... algorithm for smart antenna systems which very important for smart antenna design. The performance of LMS algorithm is compared on the basis of normalized array factor and mean square error (MSE) for ...
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Optimal Search for Minimum Error Rate Training
... unsmoothed error count is a highly non-convex objective function and therefore difficult to optimize directly; prior work offers no algorithm with a good approximation ...
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Adaptive Minimum Bit Error Rate Beamforming
... Unlike the MMSE solution (8), there exists no closed-form MBER solution. In theory, there is no guarantee that the above conjugate gradient algorithm can always find a global minimum point of the BER surface . In ...
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Mean Square Cordial Labeling of Some Snake Graphs
... admits mean square cordial labeling. In particular , mean square cordial labeling of a Triangular snake Tk, Subdivision of a triangular snake S(Tk), Quadrilateral snake QSk, Subdivision of a ...
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Generalized Minimum Perpendicular Distance Square Method of Estimation
... This procedure of transforming the original variables is done in such a way that the transformed variables sat- isfy the assumptions of the classical model. Now apply- ing MPDS method to this transformed model to ...
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