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E-raamat: Algebraic Codes for Data Transmission

(University of Illinois, Urbana-Champaign)
  • Formaat: PDF+DRM
  • Ilmumisaeg: 06-Feb-2003
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9780511074295
  • Formaat - PDF+DRM
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  • Formaat: PDF+DRM
  • Ilmumisaeg: 06-Feb-2003
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9780511074295

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The need to transmit and store massive amounts of data reliably and without error is a vital part of modern communications systems. Error-correcting codes play a fundamental role in minimising data corruption caused by defects such as noise, interference, crosstalk and packet loss. This book provides an accessible introduction to the basic elements of algebraic codes, and discusses their use in a variety of applications. The author describes a range of important coding techniques, including Reed-Solomon codes, BCH codes, trellis codes, and turbocodes. Throughout the book, mathematical theory is illustrated by reference to many practical examples. The book was first published in 2003 and is aimed at graduate students of electrical and computer engineering, and at practising engineers whose work involves communications or signal processing.

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An accessible 2003 introduction to the basic elements of algebraic codes including Reed-Solomon, trellis, turbocodes etc.
Preface xi
1 Introduction 1(19)
1.1 The discrete communication channel
2(2)
1.2 The history of data-transmission codes
4(2)
1.3 Applications
6(1)
1.4 Elementary concepts
7(7)
1.5 Elementary codes
14(3)
Problems
17(3)
2 Introduction to Algebra 20(29)
2.1 Fields of characteristic two
20 (3)
2.2 Groups
23(5)
2.3 Rings
28(2)
2.4 Fields
30(2)
2.5 Vector spaces
32(5)
2.6 Linear algebra
37(8)
Problems
45(3)
Notes
48(1)
3 Linear Block Codes 49(18)
3.1 Structure of linear block codes
49(1)
3.2 Matrix description of linear block codes
50(4)
3.3 Hamming codes
54(2)
3.4 The standard array
56(3)
3.5 Hamming spheres and perfect codes
59(3)
3.6 Simple modifications to a linear code
62(1)
Problems
63(3)
Notes
66(1)
4 The Arithmetic of Galois Fields 67(29)
4.1 The integer ring
67(3)
4.2 Finite fields based on the integer ring
70(2)
4.3 Polynomial rings
72(7)
4.4 Finite fields based on polynomial rings
79(4)
4.5 Primitive elements
83(3)
4.6 The structure of finite fields
86(6)
Problems
92 (3)
Notes
95(1)
5 Cyclic Codes 96(35)
5.1 Viewing a code from an extension field
96(3)
5.2 Polynomial description of cyclic codes
99(5)
5.3 Minimal polynomials and conjugates
104(7)
5.4 Matrix description of cyclic codes
111(2)
5.5 Hamming codes as cyclic codes
113(3)
5.6 Cyclic codes for correcting double errors
116(2)
5.7 Quasi-cyclic codes and shortened cyclic codes
118(1)
5.8 The Golay code as a cyclic code
119(4)
5.9 Cyclic codes for correcting burst errors
123(2)
5.10 The Fire codes as cyclic codes
125(2)
5.11 Cyclic codes for error detection
127(1)
Problems
128(2)
Notes
130(1)
6 Codes Based on the Fourier Transform 131(48)
6.1 The Fourier transform
131(7)
6.2 Reed-Solomon codes
138(5)
6.3 Conjugacy constraints and idempotents
143(5)
6.4 Spectral description of cyclic codes
148(4)
6.5 BCH codes
152(7)
6.6 The Peterson-Gorenstein-Zierler decoder
159(7)
6.7 The Reed-Muller codes as cyclic codes
166(3)
6.8 Extended Reed-Solomon codes
169(3)
6.9 Extended BCH codes
172(3)
Problems
175 (2)
Notes
177(2)
7 Algorithms Based on the Fourier Transform 179(49)
7.1 Spectral estimation in a finite field
179(4)
7.2 Synthesis of linear recursions
183(8)
7.3 Decoding of binary BCH codes
191(2)
7.4 Decoding of nonbinary BCH codes
193(8)
7.5 Decoding with erasures and errors
201(5)
7.6 Decoding in the time domain
206(4)
7.7 Decoding within the BCH bound
210(3)
7.8 Decoding beyond the BCH bound
213(3)
7.9 Decoding of extended Reed-Solomon codes
216(1)
7.10 Decoding with the euclidean algorithm
217(6)
Problems
223(3)
Notes
226(2)
8 Implementation 228(42)
8.1 Logic circuits for finite-field arithmetic
228(7)
8.2 Shift-register encoders and decoders
235(2)
8.3 The Meggitt decoder
237(7)
8.4 Error trapping
244(6)
8.5 Modified error trapping
250(4)
8.6 Architecture of Reed-Solomon decoders
254(4)
8.7 Multipliers and inverters
258(4)
8.8 Bit-serial multipliers
262(5)
Problems
267(2)
Notes
269(1)
9 Convolutional Codes 270(43)
9.1 Codes without a block structure
270(3)
9.2 Trellis description of convolutional codes
273(5)
9.3 Polynomial description of convolutional codes
278(4)
9.4 Check matrices and inverse matrices
282(5)
9.5 Error correction and distance notions
287(2)
9.6 Matrix description of convolutional codes
289(2)
9.7 The Wyner-Ash codes as convolutional codes
291(3)
9.8 Syndrome decoding algorithms
294(4)
9.9 Convolutional codes for correcting error bursts
298(5)
9.10 Algebraic structure of convolutional codes
303(6)
Problems
309(2)
Notes
311(2)
10 Beyond BCH Codes 313(22)
10.1 Product codes and interleaved codes
314(4)
10.2 Bicyclic codes
318(3)
10.3 Concatenated codes
321(2)
10.4 Cross-interleaved codes
323(3)
10.5 Turbo codes
326(3)
10.6 Justesen codes
329(3)
Problems
332(2)
Notes
334(1)
11 Codes and Algorithms Based on Graphs 335(40)
11.1 Distance, probability, and likelihood
336(4)
11.2 The Viterbi algorithm
340(3)
11.3 Sequential algorithms to search a trellis
343(7)
11.4 Trellis description of linear block codes
350(4)
11.5 Gallager codes
354(1)
11.6 Tanner graphs and factor graphs
355(2)
11.7 Posterior probabilities
357(2)
11.8 The two-way algorithm
359(3)
11.9 Iterative decoding of turbo codes
362(2)
11.10 Tail-biting representations of block codes
364(4)
11.11 The Golay code as a tail-biting code
368(4)
Problems
372(2)
Notes
374(1)
12 Performance of Error-Control Codes 375(43)
12.1 Weight distributions of block codes
375(8)
12.2 Performance of block codes
383(3)
12.3 Bounds on minimum distance of block codes
386(8)
12.4 Binary expansions of Reed-Solomon codes
394(5)
12.5 Symbol error rates on a gaussian-noise channel
399(4)
12.6 Sequence error rates on a gaussian-noise channel
403(3)
12.7 Coding gain
406(5)
12.8 Capacity of a gaussian-noise channel
411(3)
Problems
414 (2)
Notes
416(2)
13 Codes and Algorithms for Majority Decoding 418(45)
13.1 Reed-Muller codes
418(8)
13.2 Decoding by majority vote
426(4)
13.3 Circuits for majority decoding
430(3)
13.4 Affine permutations for cyclic codes
433(4)
13.5 Cyclic codes based on permutations
437(4)
13.6 Convolutional codes for majority decoding
441(1)
13.7 Generalized Reed-Muller codes
442(5)
13.8 Euclidean-geometry codes
447(9)
13.9 Projective-geometry codes
456(4)
Problems
460(1)
Notes
461(2)
Bibliography 463(10)
Index 473


Professor Richard E. Blahut is Head of the Department of Electrical and Computer Engineering at the University of Illinois, Urbana Champaign. He is a fellow of the Institute of Electrical and Electronics Engineers and the recipient of many prestigious awards including the IEEE Alexander Graham Bell Medal (1998); the Tau Beta Pi Daniel C. Drucker Eminent Faculty Award and the IEEE Millennium Medal. He was named a Fellow of the IBM Corporation in 1980 (where he worked for over 30 years) and was elected to the National Academy of Engineering in 1990.