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Joint source channel coding using arithmetic codes

By: Bi, Dongsheng.
Contributor(s): Hoffman, Michael W | Sayood, Khalid.
Material type: materialTypeLabelBookSeries: Synthesis lectures on communications: # 4.Publisher: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, c2010Description: 1 electronic text (viii, 69 p. : ill.) : digital file.ISBN: 9781608451494 (electronic bk.).Uniform titles: Synthesis digital library of engineering and computer science. Subject(s): Coding theory | Error-correcting codes (Information theory) | Source coding | Joing source channel coding | Arithmetic coding | Channel coding | Digital communicationsDDC classification: 003.54 Online resources: Abstract with links to resource Also available in print.
Contents:
1. Introduction -- Introduction -- Joint source and channel coding schemes -- Joint source and channel coding with arithmetic codes -- 2. Arithmetic codes -- Encoding and decoding processes -- Integer implementation of encoding and decoding with renormalization -- Encoding with integer arithmetic -- Decoding with integer arithmetic -- Overflow and underflow problems -- Optimality of arithmetic coding -- Arithmetic codes are prefix codes -- Efficiency -- Efficiency of the integer implementation -- 3. Arithmetic codes with forbidden symbols -- Error detection and correction using arithmetic codes -- Reserved probability space and code rate -- Error detection capability -- Error correction with arithmetic codes -- Viewing arithmetic codes as fixed trellis codes -- Encoding -- Decoding -- Simulations with an iid source -- Simulations with Markov sources -- Comparing scenario (a) and (b) -- Comparing scenario (b) and (c) -- 4. Distance property and code construction -- Distance property of arithmetic codes -- Bound on error events -- Using the bound to get estimate of error probability -- Determining the multiplicity Am,l -- Verification -- Complexity factors and freedom in the code design -- Complexity factors -- Freedom in the code design -- Arithmetic codes with input memory -- Memory one arithmetic codes with forbidden symbols -- Memory two arithmetic codes with forbidden symbols -- Memory three arithmetic codes with forbidden symbols -- 5. Conclusion -- Bibliography.
Abstract: Based on the encoding process, arithmetic codes can be viewed as tree codes and current proposals for decoding arithmetic codes with forbidden symbols belong to sequential decoding algorithms and their variants. In this monograph, we propose a new way of looking at arithmetic codes with forbidden symbols. If a limit is imposed on the maximum value of a key parameter in the encoder, this modified arithmetic encoder can also be modeled as a finite state machine and the code generated can be treated as a variable-length trellis code.The number of states used can be reduced and techniques used for decoding convolutional codes, such as the list Viterbi decoding algorithm, can be applied directly on the trellis.
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Mode of access: World Wide Web.

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Part of: Synthesis digital library of engineering and computer science.

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Includes bibliographical references (p. 61-69).

1. Introduction -- Introduction -- Joint source and channel coding schemes -- Joint source and channel coding with arithmetic codes -- 2. Arithmetic codes -- Encoding and decoding processes -- Integer implementation of encoding and decoding with renormalization -- Encoding with integer arithmetic -- Decoding with integer arithmetic -- Overflow and underflow problems -- Optimality of arithmetic coding -- Arithmetic codes are prefix codes -- Efficiency -- Efficiency of the integer implementation -- 3. Arithmetic codes with forbidden symbols -- Error detection and correction using arithmetic codes -- Reserved probability space and code rate -- Error detection capability -- Error correction with arithmetic codes -- Viewing arithmetic codes as fixed trellis codes -- Encoding -- Decoding -- Simulations with an iid source -- Simulations with Markov sources -- Comparing scenario (a) and (b) -- Comparing scenario (b) and (c) -- 4. Distance property and code construction -- Distance property of arithmetic codes -- Bound on error events -- Using the bound to get estimate of error probability -- Determining the multiplicity Am,l -- Verification -- Complexity factors and freedom in the code design -- Complexity factors -- Freedom in the code design -- Arithmetic codes with input memory -- Memory one arithmetic codes with forbidden symbols -- Memory two arithmetic codes with forbidden symbols -- Memory three arithmetic codes with forbidden symbols -- 5. Conclusion -- Bibliography.

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Based on the encoding process, arithmetic codes can be viewed as tree codes and current proposals for decoding arithmetic codes with forbidden symbols belong to sequential decoding algorithms and their variants. In this monograph, we propose a new way of looking at arithmetic codes with forbidden symbols. If a limit is imposed on the maximum value of a key parameter in the encoder, this modified arithmetic encoder can also be modeled as a finite state machine and the code generated can be treated as a variable-length trellis code.The number of states used can be reduced and techniques used for decoding convolutional codes, such as the list Viterbi decoding algorithm, can be applied directly on the trellis.

Also available in print.

Title from PDF t.p. (viewed on December 9, 2009).

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