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We devise new coding methods to minimize Phase Change Memory write energy. Our method minimizes the energy required for memory rewrites by utilizing the differences between PCM read, set, and reset energies. We develop an integer linear programming method and employ dynamic programming to produce codes for uniformly distributed data. We also introduce data-aware coding schemes to efficiently address...
In this paper, a predictive model for compression of mosaic image with Bayer pattern is proposed. It consists of TFNN neural network predictor and adaptive correction part based on context. As in JPEG-LS, the adaptive part of the predictor is context-based and it is used to ldquocancelrdquo the integer part of the offset due to the TFNN predictor. In the meantime, we propose a context quantization...
This paper suggests a signal processing method for finding the minimax codes which minimize the maximum redundancies over a class of sources with either a discrete or a continuous alphabet, and where relative entropy (cross entropy; discrimination information) is a criterion to measure the redundancy. A complexity analysis and numerical studies demonstrate the efficiency of the method.
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