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Journal ArticleDOI

Structural analysis of error-correcting codes for discrete channels that involve combinations of three basic error types

TLDR
It can be said that unique decodability is decidable also in the presence of errors in the class of bounded error effects channels (BEE channels), which are used to model, for instance, scattered errors and bursts of errors of any combination of the three error types.
Abstract
A nonprobabilistic mathematical model is introduced of discrete channels that involve the error types substitution, insertion, and deletion. The model is based on the novelty that errors can be expressed as strings over an alphabet of basic error symbols. Some general conditions on errors are defined which bound the error effects on messages, obtaining thus the class of bounded error effects channels (BEE channels). These channels can be used to model, for instance, scattered errors and bursts of errors of any combination of the three error types. A general notion of error-correcting code is defined and a characterization of the error-correcting codes for a given BEE channel is obtained. Then, an algorithm is presented that tests, for a given finite code (not necessarily of fixed length) and a given description of a BEE channel, whether the code is error-correcting for the channel defined by the given description. This result can be considered as an extension of the well-known theorem of Sardinas and Patterson (1953) for testing the unique decodability of a given finite code. In this sense, it can be said that unique decodability is decidable also in the presence of errors.

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Citations
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Journal ArticleDOI

A survey of error-correcting codes for channels with symbol synchronization errors

TL;DR: A comprehensive survey of error-correcting codes for channels corrupted by synchronization errors and potential applications as well as the obstacles that need to be overcome before such codes can be used in practical systems are presented.

Transducers and the Properties of Error-Detection, Error-Correction, and Finite-Delay Decodability 1

TL;DR: This work uses transducers to model noisy channels and considers a few simple transducer operations that can be used to reduce the properties of error-detection and error-correction to theTransducer property of functionality, and obtains simple polynomial-time algorithms for de- ciding these properties for regular languages.
Journal ArticleDOI

An Algebra of Discrete Channels That Involve Combinations of Three Basic Error Types

TL;DR: This paper defines an important class of BEE channels, the SID channels, which include channels that permit a bounded number of scattered errors and, possibly at the same time, a bounded burst of errors in any segment of predefined length of a message.
Journal ArticleDOI

Relationships between different error-correcting capabilities of a code

TL;DR: A simple distance is defined that generalizes the Hamming and Levenshtein distances for a certain class of SID channels to obtain a necessary and sufficient condition for the error-correcting capability that corresponds to the channel in question.
Proceedings ArticleDOI

Relationships between different error-correcting capabilities of a code

TL;DR: A simple distance is defined that generalizes the Hamming and Levenshtein distances for a certain class of SID channels to obtain a unifying necessary and sufficient condition for the error correcting capability that corresponds to the channel in question.
References
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Book

The Theory of Error-Correcting Codes

TL;DR: This book presents an introduction to BCH Codes and Finite Fields, and methods for Combining Codes, and discusses self-dual Codes and Invariant Theory, as well as nonlinear Codes, Hadamard Matrices, Designs and the Golay Code.
Book

Coding and Information Theory

TL;DR: Coding and information theory, Coding and Information theory, مرکز فناوری اطلاعات و اصاع رسانی, کδاوρزی.
Book

Theory of codes