Papers by Luis manzanedo rueda
Information Sciences, 2006
Adaptive coding techniques have been increasingly used in lossless data compression. They are sui... more Adaptive coding techniques have been increasingly used in lossless data compression. They are suitable for a wide range of applications, in which on-line compression is required, including communications, internet, e-mail, and e-commerce. In this paper, we present an adaptive Fano coding method applicable to binary and multi-symbol code alphabets. We introduce the corresponding partitioning procedure that deals with consecutive partitionings, and that possesses, what we have called, the nearly-equal-probability property, i.e. that satisfy the principles of Fano coding. To determine the optimal partitioning, we propose a brute-force algorithm that searches the entire space of all possible partitionings. We show that this algorithm operates in polynomial-time complexity on the size of the input alphabet, where the degree of the polynomial is given by the size of the output alphabet. As opposed to this, we also propose a greedy algorithm that quickly finds a sub-optimal, but accurate, consecutive partitioning. The empirical results on real-life benchmark data files demonstrate that our scheme compresses and decompresses faster than adaptive Huffman coding, while consuming less memory resources.
Lecture Notes in Computer Science, 2004
In this paper, we introduce a new approach to adaptive coding which utilizes Stochastic Learning-... more In this paper, we introduce a new approach to adaptive coding which utilizes Stochastic Learning-based Weak Estimation (SLWE) techniques to adaptively update the probabilities of the source symbols. We present the corresponding encoding and decoding algorithms, as well as the details of the probability updating mechanisms. Once these probabilities are estimated, they can be used in a variety of data encoding schemes, and we have demonstrated this, in particular, for the adaptive Fano scheme and and an adaptive entropy-based scheme that resembles the well-known arithmetic coding. We include empirical results using the latter adaptive schemes on real-life files that possess a fair degree of nonstationarity. As opposed to higher-order statistical models, our schemes require linear space complexity, and compress with nearly 10% better efficiency than the traditional adaptive coding methods.
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Papers by Luis manzanedo rueda