PROBLEMS OF INFORMATION TRANSMISSION
A translation of Problemy Peredachi Informatsii


Volume 15, Number 2, April–June, 1979
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CONTENTS

 

Linear Transmission of Gaussian Messages over a Nonstationary Gaussian Channel with Feedback
I. A. Ovseevich and M. S. Pinsker
pp. 85–99

Abstract—Necessary and sufficient existence conditions are found for linear transmission of a Gaussian message over a discrete (in time) memoryless Gaussian channel with complete feedback, under the condition that the transmitted and reproduced messages have a specified covariance function. An algorithm for this transmission is given; a transmission algorithm that minimizes the mean-square error (MSE) is indicated, and the value of this error is written out.

 

Bounds on the Error Probability for Certain Ensembles of Random Codes
A. G. D'yachkov
pp. 99–108

Abstract—Two classes of random codes are considered, for which (unlike the standard situation in information theory) the code words are not independent. These codes arise in investigating Boolean and linear models of the design of screening experiments. Upper and lower bounds are obtained for the mean error probability over the ensemble of codes, for transmission over a memoryless channel and with maximum-likelihood decoding.

 

Pseudostochastic Coding for Error Detection
L. M. Fink and S. A. Mukhametshina
pp. 108–110

Abstract—It is shown that it is possible to replace random sequences for universal coding in data transmission systems with feedback by pseudorandom sequences.

 

Capacity for a Sum of Broadcast Channels
G. Sh. Poltyrev
pp. 111–114

Abstract—The article considers a discrete broadcast channel with two receivers, each constituent of which is a sum of some number of discrete memoryless channels (components). The components form broadcast channels that degrade in different directions. The capacity is determined for a broadcast channel of this type.

 

Coding of Sources on the Basis of Observations with Incomplete Information
S. I. Gel'fand and M. S. Pinsker
pp. 115–125

Abstract—The article considers the problem of recovering the messages of a source on the basis of the encoded messages of several sources that are correlated with it.

 

Correction of Error Bursts and Independent Errors using Generalized Concatenated Codes
V. A. Zinov'ev and V. V. Zyablov
pp. 125–134

Abstract—It is shown that a cascade decoding algorithm that realizes its code distance makes it possible to simultaneously correct both error bursts and independent errors that occur in addition to bursts. Lower bounds are given for the guaranteed lengths of the bursts to be corrected and for the guaranteed number of independent errors that can be corrected.

 

Coding of a Source with Unknown but Ordered Probabilities
B. Ya. Ryabko
pp. 134–138

Abstract—The article deals with the problem of optimum coding of a source for whose symbols it is known only that they are arranged in decreasing order of probability. On the basis of the resultant code, a design for a universal retrieval system is proposed and a hypothesis that accounts for Zipf’s law is advanced.

 

Weight Spectra of Some Classes of Binary Cyclic Codes
V. I. Tairyan
pp. 139–144

Abstract—Formulas are derived for the weight spectra and code distances of some classes of binary cyclic codes.

 

Efficiency of Discrimination Algorithm for Orthogonal Signals with Unknown Parameters
A. P. Trifonov
pp. 144–152

Abstract—The probabilities of incorrect decisions in discriminating signals with unknown nonenergy parameters in Gaussian noise are determined. The efficiency loss as a result of lack of knowledge of the parameters is estimated. Results of experimental verification of the formulas are given.

 

Asymptotic Behavior of the Number of Types of Equivalent Binary Connection Matrices
Yu. L. Sagalovich
pp. 152–158

Abstract—An asymptotic formula is derived for the number of types of binary matrices that are equivalent relative to permutations of rows and columns and/or inversion of columns. The asymptotic behavior is also obtained for the case of nonsingular matrices, for which an exact formula is as yet unknown.

 

On Error Probability in Recognition Problems with a Random Vocabulary
V. S. Fain
pp. 159–160

Abstract—For recognition problems in which the set of objects to be recognized is not fixed in advance, but only their type is known (e.g., in the handwriting-analysis problem), it is not possible to specify a priori the value of the error probability inherent in the algorithm employed. On the basis of the analogy between such problems and the problem of transmission of information over a noisy channel with random coding, it is shown that it is possible to set up an upper bound for the mean error probability (over the sets) when the maximum-likelihood method of recognition is employed. A working formula for this bound is given for one particular case.

 

Vladimir Ivanovich Siforov’s Seventy-Fifth Birthday
pp. 161–162