scholarly journals Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty

2021 ◽  
Vol 279 ◽  
pp. 02003
Author(s):  
Ivan Nikishin ◽  
Vladimir Marchuk ◽  
Igor Shrayfel ◽  
Ilya Sadrtdinov
Keyword(s):  
Additive Noise ◽  
A Priori ◽  
Signal Extraction ◽  
Statistical Characteristics ◽  
Practical Implementation ◽  
Sample Length ◽  
Complex Signals ◽  
Useful Signal ◽  
A Priori Uncertainty ◽  
Measured Process

The paper discusses the issues of practical implementation of increasing the accuracy of signal extraction, which is achieved by eliminating the «flip» of the approximating function when dividing the measured process into intervals under conditions of a priori uncertainty about the signal function, which significantly increases the error of allocating a useful signal. The probability of a «flip» of the approximating function depends significantly on the variance of the additive noise and the sample length. The use of the proposed methods and their software implementation makes it possible to increase the accuracy of the useful signal extraction up to 30 percent in the absence of a priori information about the function of the measured process for complex signals and at least 20% for simpler ones. The use of the proposed methods will significantly increase the processing efficiency in the conditions of a priori uncertainty about the function of the measured process (useful signal) and the statistical characteristics of the additive noise components.

scholarly journals Research of the probability of the "flip" of approximating function during the processing of measurement results

2019 ◽  
Vol 104 ◽  
pp. 02003
Author(s):  
Vladimir Marchuk ◽  
Dmitry Chernyshov ◽  
Ilya Sadrtdinov ◽  
Alexander Minaev
Keyword(s):  
Confidence Intervals ◽  
Additive Noise ◽  
A Priori ◽  
Rate Of Change ◽  
Statistical Characteristics ◽  
Sample Length ◽  
Signal Function ◽  
Measurement Results ◽  
Processing Of Measurement Results ◽  
A Priori Uncertainty

The paper presents the results of the studies of the probability of a “flip” of the approximating function when processing the measurement results under conditions of a priori uncertainty about the signal function and the statistical characteristics of additive noise. It is analytically proved that the confidence intervals of the probability of the absence and the presence of a “flip” are equal, which is confirmed by the experimental results. The dependences of the “flipping” of the approximating function on the sample length, the dispersion of additive noise and the rate of change of the function itself are obtained.

scholarly journals Special aspects of using a new non-stationary random processes analysis approach in the conditions of a priori uncertainty of the useful signal function

2019 ◽  
Vol 30 ◽  
pp. 03002
Author(s):  
Vladimir Marchuk
Keyword(s):  
Additive Noise ◽  
High Efficiency ◽  
A Priori ◽  
Statistical Characteristics ◽  
Signal Function ◽  
Useful Signal ◽  
Priori Information ◽  
The Time Domain ◽  
A Priori Uncertainty ◽  
Stationary Random Processes

The paper considers the use of a new method of signal processing in the time domain under conditions of a limited amount of a priori information about the useful signal function and the statistical characteristics of additive noise. Research have shown its high efficiency in processing signals both local and global, using it to detect anomalous measurements, eliminating the systematic component in the case of a onesided law of the distribution of additive noise and a number of others.

Method for measuring distortions of a speech signal during its transmission over a communication channel to a biometric identification system

2020 ◽  
pp. 65-72
Author(s):  
V. V. Savchenko ◽  
A. V. Savchenko
Keyword(s):  
Speech Signal ◽  
Communication Channel ◽  
Speaker Identification ◽  
A Priori ◽  
Small Samples ◽  
Practical Implementation ◽  
Identification System ◽  
New Information ◽  
Discrimination Criterion ◽  
A Priori Uncertainty

This paper is devoted to the presence of distortions in a speech signal transmitted over a communication channel to a biometric system during voice-based remote identification. We propose to preliminary correct the frequency spectrum of the received signal based on the pre-distortion principle. Taking into account a priori uncertainty, a new information indicator of speech signal distortions and a method for measuring it in conditions of small samples of observations are proposed. An example of fast practical implementation of the method based on a parametric spectral analysis algorithm is considered. Experimental results of our approach are provided for three different versions of communication channel. It is shown that the usage of the proposed method makes it possible to transform the initially distorted speech signal into compliance on the registered voice template by using acceptable information discrimination criterion. It is demonstrated that our approach may be used in existing biometric systems and technologies of speaker identification.

Information Processing Systems in UAV Based on Bayesian Filtering in Conditions of Uncertainty

2020 ◽  
Vol 12 (4) ◽  
pp. 42-59
Author(s):  
Rinat Galiautdinov
Keyword(s):  
Information Processing ◽  
Degrees Of Freedom ◽  
Adaptive Filters ◽  
A Priori ◽  
Practical Implementation ◽  
Bayesian Filtering ◽  
Math Model ◽  
Digital Implementation ◽  
Estimation Algorithms ◽  
A Priori Uncertainty

In this article, the author considers the possibility of applying modern IT technologies to implement information processing algorithms in UAV motion control system. Filtration of coordinates and motion parameters of objects under a priori uncertainty is carried out using nonlinear adaptive filters: Kalman and Bayesian filters. The author considers numerical methods for digital implementation of nonlinear filters based on the convolution of functions, the possibilities of neural networks and fuzzy logic for solving the problems of tracking UAV objects (or missiles), the math model of dynamics, the features of the practical implementation of state estimation algorithms in the frame of added additional degrees of freedom. The considered algorithms are oriented on solving the problems in real time using parallel and cloud computing.

ANALYSIS OF THE INFLUENCE OF A PRIORI UNCERTAINTY RELATING TO THE DISPERSION OF ADDITIVE NOISE ON THE OPERATION OF SIGNAL PARAMETERS ESTIMATION ALGORITHMS

2021 ◽  
Author(s):  
Н.Е. ПОБОРЧАЯ
Keyword(s):  
Nonlinear Filtering ◽  
Additive Noise ◽  
A Priori ◽  
Estimation Procedure ◽  
Parameters Estimation ◽  
Joint Estimation ◽  
Regularizing Algorithm ◽  
Estimation Algorithms ◽  
True Variance ◽  
A Priori Uncertainty

Проведен анализ работы регуляризующего алгоритма и процедуры нелинейной фильтрации в условиях неточного знания величины дисперсии аддитивного шума и анализ их вычислительной сложности. С помощью регуляризующих алгоритмов на фоне аддитивного и фазового шума оценивались параметры сигнала квадратурной амплитудной модуляции: сдвиг частоты, постоянные составляющие квадратур сигнала, амплитудный и фазовый дисбаланс, амплитуда и фаза сигнала. Показано, что их сложность ниже, чем у известной процедуры совместного оценивания, а регуляризующий алгоритм устойчивее процедуры нелинейной фильтрации к отклонению дисперсии аддитивного шума от истинных значений. Analysis of the operation of regularizing algorithm and procedure of nonlinear filtering in conditions of the imprecise value of the variance of the additive noise and analysis of their computational complexity were carried out. Using regularizing these algorithms against the background of additive and phase noise, the following parameters of the quadrature amplitude modulation signal were estimated: frequency shift, constant components of the signal quadrature, amplitude and phase imbalance, amplitude and phase of the signal. It is shown that their complexity is lower than that of the well-known joint estimation procedure, and also that the regularizing algorithm is more resistant to deviations from the true variance of the additive noise than the nonlinear filtering procedure.

scholarly journals Determining the Initial Orientation for Navigation and Measurement Systems of Mobile Apparatus in Reforestation

Inventions ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 56 ◽  
Author(s):  
Sokolov ◽  
Novikov ◽  
Ivetić
Keyword(s):  
Angular Velocity ◽  
High Precision ◽  
Additive Noise ◽  
A Priori ◽  
Initial Orientation ◽  
Statistical Characteristics ◽  
Measurement Systems ◽  
Computational Costs ◽  
Mobile Objects

This paper considers the method of determining the initial orientation of the navigation and measuring complexes of mobile objects. The method is based on analytical gyrocompassing, using angular velocity sensors whose measurements are distorted by additive noise, with a priori uncertain statistical characteristics. The proposed approach requires small computational costs and can be effectively used in the development of high-precision systems of initial orientation of navigation–measurement systems of various mobile objects.

RESEARCH OF THE ADAPTIVE FINITE-TIME SIGNAL FILTERING METHOD AND COMPARISON WITH THE ADAPTIVE KALMAN FILTERING

2021 ◽  
Vol 2 (28) ◽  
pp. 9-14
Author(s):  
I. V. Svetlov ◽  
◽  
Yu. P. Ivanov ◽  
Keyword(s):  
Key Words ◽  
Kalman Filtering ◽  
Correlation Functions ◽  
Finite Time ◽  
High Stability ◽  
A Priori ◽  
Time Signal ◽  
Filtering Method ◽  
Useful Signal ◽  
A Priori Uncertainty

The method of optimal characteristics, high stability and simplicity of the algorithm is presented. The method under consideration is compared with Kalman filtering. Cases of a priori uncertainty with unknown correlation functions of the noise and the useful signal are considered. Key words: finite-time filtering, Kalman filtering, a priori uncertainty.

scholarly journals Determination of the Probability Density Function of the Mixture Signal and Additive Noise under Influence of Multiplicative Noise

2021 ◽  
Vol 2096 (1) ◽  
pp. 012154
Author(s):  
V M Artyushenko ◽  
V I Volovach
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Additive Noise ◽  
Statistical Characteristics ◽  
Arbitrary Distribution ◽  
Functional Connection ◽  
Useful Signal ◽  
Normal Law ◽  
Phase Distortions

Abstract Issues related to effect of multiplicative (modulating) (otherwise amplitude distortions) and additive noises on processed signal are considered. Analysis of statistical characteristics of probability density function (PDF) of instantaneous signal values against background of modulating interference is carried out. Expressions of the joint PDF envelope, phase and instantaneous signal values are obtained, for the case of only phase distortions, as well as the case when fluctuations in amplitude and phase are independent of each other. It is noted that in the second case, with the independence of phase and amplitude distortions, the PDF of the signal, first of all, is determined by the PDF of its instantaneous values and practically does not depend on the PDF of the signal phase. Expressions are obtained for the PDF useful signal and the most common PDF envelope when affecting the signal with modulating noise for deep phase distortions and for its uniform distribution over the interval (0, 2π). In addition, for the case of some functional relationship of phase and amplitude fluctuations, the expression for PDF instantaneous signal values is defined. The presence of such a functional connection allows calculating the PDF of the signal through the statistical characteristics of its envelope. It is obtained that PDF of mixture of signal and additive noise contains arbitrary distribution of phase and amplitude, as well as arbitrary law of distribution of envelope of processed signal. It is obtained that weight coefficients are determined by derivative of characteristic function of amplitude distortion in case when PDFs of said mixture are distributed according to normal law and functional connection exists between amplitude and phase distortions.

Method of frequency-time localization of complex signals under a priori uncertainty conditions

2008 ◽  
Vol 51 (3) ◽  
pp. 238-245
Author(s):  
V. N. Shevchenko ◽  
G. G. Vertogradov ◽  
P. N. Vikulov
Keyword(s):  
A Priori ◽  
Complex Signals ◽  
A Priori Uncertainty
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