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Book ChapterDOI

Adaptive Lossless Data Compression over a Noisy Channel

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TLDR
This work presents a new model of error resilient communication where even though errors may not be detected, there are strong guarantees that their effects will not propagate.
Abstract
With dynamic communication a sender and receiver work in a “lock-step” cooperation to maintain identical copies of a dictionary D (which is constantly changing). A key application of dynamic communication is adaptive data compression. A potential drawback of dynamic communication is error propagation (that causes the sender and receiver dictionaries to diverge and possibly corrupt all data to follow). Protocols that require the receiver to request re-transmission from the sender when an error is detected can be impractical for many applications where such two way communication is not possible or self-defeating (e.g., with data compression, re-transmission is tantamount to losing the data that could have been transmitted in the mean time). We present a new model of error resilient communication where even though errors may not be detected, there are strong guarantees that their effects will not propagate.

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Citations
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Book ChapterDOI

Massively Parallel Systolic Algorithms for Real-Time Dictionary-Based Text Compression

TL;DR: This work presents massively parallel approaches for real-time textual substitution, where repeated substrings are replaced by pointers into a dynamically changing dictionary of strings in a lossless data compression method.
References
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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

Compression of individual sequences via variable-rate coding

TL;DR: 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.
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

A Technique for High-Performance Data Compression

Welch
- 01 Jun 1984 - 
TL;DR: A new compression algorithm is introduced that is based on principles not found in existing commercial methods in that it dynamically adapts to the redundancy characteristics of the data being compressed, and serves to illustrate system problems inherent in using any compression scheme.
Book

Data compression: methods and theory

TL;DR: Books and internet are the recommended media to help you improving your quality and performance.