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Journal ArticleDOI

Compression of individual sequences via variable-rate coding

TLDR
The proposed concept of compressibility is shown to play a role analogous to that of entropy in classical information theory where one deals with probabilistic ensembles of sequences rather than with individual sequences.
Abstract
Compressibility of individual sequences by the class of generalized finite-state information-lossless encoders is investigated. These encoders can operate in a variable-rate mode as well as a fixed-rate one, and they allow for any finite-state scheme of variable-length-to-variable-length coding. For every individual infinite sequence x a quantity \rho(x) is defined, called the compressibility of x , which is shown to be the asymptotically attainable lower bound on the compression ratio that can be achieved for x by any finite-state encoder. This is demonstrated by means of a constructive coding theorem and its converse that, apart from their asymptotic significance, also provide useful performance criteria for finite and practical data-compression tasks. The proposed concept of compressibility is also shown to play a role analogous to that of entropy in classical information theory where one deals with probabilistic ensembles of sequences rather than with individual sequences. While the definition of \rho(x) allows a different machine for each different sequence to be compressed, the constructive coding theorem leads to a universal algorithm that is asymptotically optimal for all sequences.

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Citations
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Journal ArticleDOI

Variable rate vector quantization for speech, image, and video compression

TL;DR: Three variable-rate vector quantizer systems are applied to speech, image, and video sources and compared to standard vector quantization and noiseless variable- rate coding approaches, providing significant performance improvements for subband speech coding, predictive image coding, and motion-compensated video.
Journal ArticleDOI

Using artificial intelligence techniques for COVID-19 genome analysis

TL;DR: Results suggest that SPM and mutation analysis techniques can reveal interesting information and patterns in COVID-19 genome sequences to examine the evolution and variations in CO VID-19 strains respectively.
Book ChapterDOI

Augmenting Suffix Trees, with Applications

TL;DR: This paper considers one algorithmic problem from each of these areas and presents highly efficient (linear or near linear time) algorithms for both problems, relying on augmenting the suffix tree, a fundamental data structure in string algorithmics.
Journal ArticleDOI

A parallel vector quantization processor eliminating redundant calculations for real-time motion picture compression

TL;DR: A parallel vector-quantization (VQ) processor has been developed aiming at real-time compression of motion pictures using a 0.35-/spl mu/m triple-metal CMOS technology that employs a new search algorithm for VQ encoding to reduce hardware volume.
Journal ArticleDOI

Adaptive Huffman coding of 2-D DCT coefficients for image sequence compression

TL;DR: A new approach to adaptive Huffman coding of 2-D DCT coefficients for image sequence compression based on the popular motion-compensated interframe coding, which employs self-switching multiple Huffman codebooks for entropy coding of quantized transform coefficients.
References
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Book

Information Theory and Reliable Communication

TL;DR: This chapter discusses Coding for Discrete Sources, Techniques for Coding and Decoding, and Source Coding with a Fidelity Criterion.
Journal ArticleDOI

A universal algorithm for sequential data compression

TL;DR: The compression ratio achieved by the proposed universal code uniformly approaches the lower bounds on the compression ratios attainable by block-to-variable codes and variable- to-block codes designed to match a completely specified source.
Journal ArticleDOI

On the Complexity of Finite Sequences

TL;DR: A new approach to the problem of evaluating the complexity ("randomness") of finite sequences is presented, related to the number of steps in a self-delimiting production process by which a given sequence is presumed to be generated.
Journal ArticleDOI

Coding theorems for individual sequences

TL;DR: The finite-state complexity of a sequence plays a role similar to that of entropy in classical information theory (which deals with probabilistic ensembles of sequences rather than an individual sequence).
Journal ArticleDOI

On Information Lossless Automata of Finite Order

TL;DR: The application of the tests to finite deterministic automata is discussed and a method of constructing a decoder for a given finite automaton that is information lossless of finite order, is described.