A translation of Problemy Peredachi Informatsii

Volume 25, Number 3, July–September, 1989
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Signal Delay Estimation in the Presence of Corrupting Parameters
G. K. Golubev
pp. 173–180

Abstract—The delay estimation problem is considered for a signal with an inexactly defined shape observed in the presence of white Gaussian noise. For high signal/noise ratios, the risks of the delay estimators are computed and their asymptotic normality is established.


Optimal Estimation Accuracy of Nonsmooth Images
A. B. Tsybakov
pp. 180–191

Abstract—We consider the estimation of nonsmooth $N$-dimensional images in the presence of noise. The image is a nonstochastic function which is smooth everywhere except on a certain number of discontinuity surfaces (lines). Order-unimprovable estimation accuracy is established for such images and an estimator is proposed on which this accuracy is attained.


Minimax Estimation of the Solution of an Ill-Posed Convolution Type Problem
M. S. Ermakov
pp. 191–200

Abstract—Asymptotically minimax estimators are constructed for the solution of convolution type equations with a random right-hand side containing a stationary random noise. The asymptotic risks of the asymptotically minimax estimators and the Tikhonov regularizing estimators are studied for a number of cases.


Model Representability of Methods for the Analysis of the Dependence Structure of Data
L. G. Malinovskii
pp. 201–211

Abstract—In the spirit of the substantive approach to probabilistic and statistical methods of data analysis, we argue in support of the relevance of what is defined as model representability of data analysis methods. Analyzing the model representability of various algorithms that identify the relationship and dependence structures of data, we show that the algorithm that determines the dependence structure by testing for zero in the inverse covariance matrix corresponds to a poorly interpretable model. A principal-component model is proposed for the analysis of the dependence structure. A number of algorithms and models are described for the analysis of the dependence and relationships structure of data.


Delayed Epsilon-Entropy of a Noisy Gaussian Message with Small Reproduction Error
A. K. Gorbunov and M. S. Pinsker
pp. 212–218

Abstract—We compute the delayed epsilon-entropy (rate distortion function) of a Gaussian message in the presence of Gaussian noise, using mean-square reproduction accuracy criterion.


Concatenated Codes in Euclidean Space
V. A. Zinoviev, S. N. Litsyn, and S. L. Portnoy
pp. 219–228

Abstract—Concatenated code construction and decoding methods are considered from a single viewpoint for codes on a sphere or inside a sphere of a given radius in a Euclidean space. These methods describe an approach to the construction of coding/modulation systems.


Stack Algorithm in a Local Area Network with Errors in the Channel
B. A. Tsybakov and S. P. Fedortsov
pp. 229–240

Abstract—Several random multiple access algorithms are proposed for controlling packet transmission in a local area communication network with errors in the channel. The maximum rate and the mean delay are determined for each algorithm. The dependence of these characteristics on channel error probabilities is studied. Some recommendations are made regarding the choice of the control algorithm and some network parameters.


Some Properties of Open Queueing Networks
S. G. Foss
pp. 241–246

Abstract—Some monotonicity and ergodicity properties are proved for open queueing systems.


A Subclass of Binary Goppa Codes
N. A. Shekhunova, S. V. Bezzateev, and E. T. Mironchikov
pp. 247–250

Abstract—The subclass of binary separable Goppa codes is described. Codes from this subclass have better parameters than any of the known codes.


Decoding Complexity Bound for Linear Block Codes
E. A. Kruk
pp. 251–254

Abstract—A new complexity bound is derived for maximum-likelihood decoding of linear block codes in a memoryless $q$-ary symmetric channel. The bound is the best among all known bounds in the entire range of code rates.


New Optimal Ensembles of Nonlinear Binary Sequences
B. Zh. Kamaletdinov
pp. 254–257

Abstract—We construct a new class of ensembles of nonlinear binary sequences with minimum attainable level of the maximum correlation in the family. The ensembles are shown to have certain desirable properties compared to known ensembles.