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Data compression and definability of types in stable and dependent formulas.
We consider the computational aspects of lossy data compression problem, where the compression error is determined by a cover of the data space. We propose an algorithm which reduces the number of par...
Consider the decentralized estimation of an unknown parameter by bandwidth constrained sensor network with a fusion center. Local sensors make observations which are linearly scaled versions of these ...
Abstract: Huffman compression is a statistical, lossless, data compression algorithm that compresses data by assigning variable length codes to symbols, with the more frequently appearing symbols give...
Abstract: We propose a rigorous analysis approach for the subset sum problem in the context of lossless data compression, where the phase transition of the subset sum problem is directly related to th...
This paper proposes to use compression-based similarity measures to cluster spectral signatures on the basis of their similarities. Such universal distances estimate the shared information between tw...
In this paper we use ternary representation of numbers for compressing text data. We use a binary map for ternary digits and introduce a way to use the binary 11-pair, which has never been use for co...
We investigate the use of the MOPED algorithm (\cite{MOPED1}) for data compression and faster evaluation of likelihood functions. Since MOPED only guarantees maintaining the Fisher matrix of the likel...
This article describes a technique of using a trigonometric function and combinatorial calculations to code or transform any finite sequence of binary numbers (0s and 1s) of any length to a unique set...
We draw a certain analogy between the classical information–theoretic problem of lossy data compression (source coding) of memoryless information sources and the statistical mechanical behavior of a c...

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