Test Methods for Signal Reconstruction of Linear Stationary Systems

The test methods designed for mathematical reconstruction of input signals of linear stationary information processing systems from distorted and noisy output signals are proposed and analyzed. It is shown that the use of test data allows one to carry out a non-blind reconstruction without determini...

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Bibliographic Details
Published inJournal of communications technology & electronics Vol. 68; no. 7; pp. 732 - 747
Main Author Novikov-Borodin, A. V.
Format Journal Article
LanguageEnglish
Published Moscow Pleiades Publishing 01.07.2023
Springer
Springer Nature B.V
Subjects
Communications Engineering
Data processing
Engineering
Ill-conditioned problems (mathematics)
Networks
Noise levels
Regularization
Signal reconstruction
Theory and Methods of Signal Processing
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Summary:The test methods designed for mathematical reconstruction of input signals of linear stationary information processing systems from distorted and noisy output signals are proposed and analyzed. It is shown that the use of test data allows one to carry out a non-blind reconstruction without determining the hardware functions of processing systems, which, in general, can belong to the class of generalized functions. The features of the use of the regularization technique in test methods are considered when solving ill-posed and ill-conditioned problems of reconstruction of real non-deterministic signals. The criteria for selecting test signals are analyzed. The results of numerical experiments on the restoration of one-dimensional signals and two-dimensional images at different noise levels are presented.
ISSN:1064-2269
1555-6557
DOI:10.1134/S1064226923070082