{"id":18,"date":"2020-11-16T16:03:25","date_gmt":"2020-11-16T13:03:25","guid":{"rendered":"https:\/\/decoders-zolotarev.ru\/en\/?page_id=18"},"modified":"2021-04-19T00:41:11","modified_gmt":"2021-04-18T21:41:11","slug":"books","status":"publish","type":"page","link":"https:\/\/decoders-zolotarev.ru\/en\/books\/","title":{"rendered":"Books"},"content":{"rendered":"

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Optimization Coding Theory and Multithreshold Algorithms<\/span><\/strong><\/p>\n

\"\"V.V. Zolotarev, Y.B. Zubarev, G.V. Ovechkin<\/u><\/b><\/p>\n

This work sets out the basic principles of modern error-correction coding optimization theory, before moving on directly to consider multithreshold decoding (MTD) algorithms. These iterative algorithms, with each symbol correction iteration, always find decisions of strictly increasing likelihood, and can achieve optimum results that would normally require exhaustive search of all possible code words.<\/p>\n

It reviews the capabilities of symbolic codes, discovered by the authors, and the corresponding, simple-toimplement special symbolic MTD decoders, which are easier and more efficient than all other known methods of decoding non-binary codes. Concatenated parallel-type arrangements and other configurations that enhance the efficiency of MTD are proposed. The efficiency limits of real codes with a code rate close to channel capacity, i.e. when R\u2248C, are evaluated. The effectiveness and complexity of error-correction procedures in software and hardware implementation are assessed.<\/p>\n

This work will be of interest to experts in the field of coding theory, communication system developers, and undergraduate and postgraduate students in relevant disciplines.<\/p>\n

First published in Switzerland in 2015 by ITU<\/b><\/p>\n

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Coding Theory as a Simple Optimal Decoding near Shannon’s Bound<\/span><\/strong><\/p>\n

\"\"V.V. Zolotarev,<\/u><\/b><\/p>\n

Optimization Theory of error-correcting coding — is a new «quantum mechanics» of information theory
\n<\/u><\/b><\/p>\n

Theoretical and applied results of modern coding theory are presented as a problem of search global extremum of the functionals in the discrete spaces.<\/p>\n

Various methods of simple error correction are considered for maximum possible noise level. It is shown that the multithreshold decoders (MTD), different versions of the Viterbi algorithms (VA) and other new coding methods successfully have solved at high technological level the main problem of information theory \u2013 a simple and effective decoding in close vicinity to the Shannon’s bound.<\/p>\n

This new \u00abquantum mechanics\u00bb of information theory is named Optimization Theory (OT) of error-correcting coding.<\/p>\n

For specialists in the field of communication systems, engineers, undergraduate, graduate and postgraduate students of mathematics and radio engineering departments.<\/p>\n

Publisher: Hot Line — Telecom, 2019<\/b><\/p>\n

Download the book!<\/span><\/b><\/a><\/b>[\/vc_column_text][vc_empty_space height=»21px»][vc_separator][\/vc_column][\/vc_row][vc_row gap=»15″ equal_height=»yes»][vc_column width=»1\/2″][vc_column_text]<\/p>\n

Problems and Discoveries\u00a0of the Optimization Theory\u00a0for Coding near Shannon\u2019s Bound\u00a0(OT in illustrations)<\/strong><\/p>\n

\"\"<\/u><\/b><\/p>\n

N.A. Kuznetsov,
\nV.V. Zolotarev,
\nY.B. Zubarev,
\nG.V. Ovechkin,\u00a0R.R. Nazirov, S.V. Averin<\/strong><\/span><\/p>\n

The theoretical and applied results of the modern noiseproof coding theory are\u00a0summarized in a popular form, using extensive illustrative material as a problem of searching\u00a0for the global extremum of the functional in discrete spaces.<\/p>\n

The authors propose the simplest algorithms for decoding of all channels classes with\u00a0independent character distortions and with a linear of the code length complexity. The decoding\u00a0error probabilities correspond to the best possible veracity levels, which is provided usually only\u00a0by optimal full searching error correction methods in noisy channels. It is extremely important\u00a0also that these highest characteristics of algorithms developed by Optimization Theory (OT) can\u00a0be achieved even very close to the Shannon\u2019s bound.<\/p>\n

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To translators and editors-2<\/a>\u00a0OPTIMAL DECODING ALGORITHMS\u00a0BY ZOLOTAREV<\/strong><\/p>\n

\"\"<\/u><\/b>V.V. Zolotarev
\n<\/strong><\/span><\/p>\n

On the basis of Optimization Theory (OT) of noise-proof coding, fundamentally new methods of message decoding for all classical channel models are described. The created multithreshold decoders (MTD) with theoretically minimal complexity provide optimal reliability even \u00a0near \u00a0Shannon\u2019s bound.<\/p>\n

Software platforms are available to readers and allow them to study the characteristics of specific new algorithms.<\/p>\n

The features of Viterbi algorithm (VA) new versions for block codes are discussed. \u00a0It is shown that according to united criterion «noise-proof\u2013veracity\u2013complexity», OT algorithms have no any competitors.<\/p>\n

It is pointed out that the absolute global leadership of OT is determined by synergistic acceleration of its development, due to the close interaction of a fine original theory and special innovative software, which has no any analogues in the world.<\/p>\n

For specialists in the field of communication systems, undergraduates, as well as graduate students of mathematical and radio engineering faculties and universities.<\/p>\n

Download the book<\/span><\/b><\/a><\/b><\/p>\n

From scientific editors<\/a><\/div>\n
From the author<\/a><\/div>\n
Conclusion<\/a><\/div>\n
To translators and editors<\/a><\/div>\n

[\/vc_column_text][vc_empty_space height=»21px»][vc_separator][\/vc_column][\/vc_row][vc_row gap=»15″ equal_height=»yes»][vc_column width=»1\/2″][vc_empty_space height=»21px»][vc_separator][\/vc_column][\/vc_row][vc_row gap=»15″ equal_height=»yes»][vc_column width=»1\/2″][vc_empty_space height=»21px»][vc_separator][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"

[vc_row gap=»15″ equal_height=»yes»][vc_column width=»1\/2″][vc_column_text] Optimization Coding Theory and Multithreshold Algorithms V.V. Zolotarev, Y.B. Zubarev, G.V. Ovechkin This work sets out the basic principles of modern error-correction coding optimization theory, before moving on directly to consider multithreshold decoding (MTD) algorithms. These iterative algorithms, with each symbol correction iteration, always find decisions of strictly increasing likelihood, and […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"full-width-page.php","meta":[],"yoast_head":"\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n