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Error Entropy and Mean Square Error Minimization for Lossless Image Compression
2006 International Conference on Image Processing, 2006In this paper, the minimum error entropy (MEE) criterion is considered as an alternative to the mean square error (MSE) criterion in obtaining predictor coefficients for lossless still image coding. Estimation of the error entropy is done using Renyi's formula.
Peter E. William, Michael W. Hoffman
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Steady-state error in adaptive mean-square minimization
IEEE Transactions on Information Theory, 1970This paper considers the steady-state mean-square error when an adaptive linear estimator is used on a stationary time series. The estimator weights are adjusted periodically by moving a small increment in the direction of the estimated gradient. Under very general conditions the asymptotic mean-square error is bounded and under more restrictive ...
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Mean square error minimization using interpolative block truncation coding algorithms
2010 2nd International Conference on Education Technology and Computer, 2010Block Truncation Coding (BTC) is one of spatial coding techniques of images. This technique has a simple and fast algorithm which achieves constant bit rate of 2 bits per pixel. The compression ratio may be improved by coding only half of the bits in the BTC bit plane of each block; the other half will be interpolated at the receiver. The resulting bit
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Mean-Square Error Minimization of Boiling Reactor Noise
Nuclear Science and Engineering, 1962An analytical approach is taken to develop a model of an optimum linear control system for a linearized approximation to a boiling water reactor. The optimization criterion used is the minimization of the mean-square error of the random fluctuation in the output variable resulting from boiling voids.
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