Algorithm for Simplifying Procedures for Digital Measurement of Signal Parameters and Reducing Signal Errors

In the article, the determination of the number of digital measurements of integral parameters of signals and the error that occurs during the conversion is analyzed. The determination of the number of digital measurements of the integral parameters of signals and the error arising during the conversion are analyzed. Arbitrary curves are usually presented graphically. Therefore, after decomposing such signals into Fourier series (by graph-analytical method), determination of parameters is brought to one of the considered cases. From the results, it can be seen that in practical cases it is possible to estimate the methodological error based on the amplitude and phase parameters of the measured signal. It forms the basis of the engineering methodology for designing the considered systems. For this purpose, theoretical studies and experiments were carried out in the MatLab software environment and positive results were obtained. Digital signal processing is a field of science and technology that studies signal and image processing algorithms common to different disciplines based on mathematical methods. The educational and methodological manual is intended—for studying both general mathematical algorithms and digital signal processing methods, and for obtaining knowledge for solving specific real-life problems, for example, in applications that implement optimal reception and processing of signals—studying the properties of discrete orthogonal transformations and applying them to improve the efficiency of signal and image processing—obtaining knowledge for the design of modern information systems and networks, in which fast computational algorithms based on spectral representations are widely used, and digital computing technology is used as processing tools. Digital signal processing is a technology that implements a huge range of applications, including infocommunications, space and military systems, medicine, archaeology, infomedia, and much more. The use of a variety of mathematical algorithms for signal processing, corresponding hardware and software makes it possible to create modern automated industrial systems of a new industrial stage in the development of society. The difference between digital signal processing and the classical analog theory of signal processing is that the processed signal in digital signal processing is a numerical sequence. Processing is carried out using operations on numbers. In this case, continuous signals are converted into a sequence of samples, i.e., a discrete signal. After discrete processing, its result is again converted into a continuous signal. For many information systems, real-time processing operations are preferred. In this case, the system response samples are calculated at the same frequency as the continuous signal sampling samples. Discrete processing of continuous signals and images in real time is a typical situation in communication systems, radar, sonar, and automated information processing systems for military purposes. The reliability and efficiency of such systems are largely determined by the use of fast computational digital algorithms for processing source data. A compact disc player (CD player) is another example, where the input analog processed signal is stored digitally on a CD and the output signal is provided in real time. DSP is widely used in systems with optimal signal processing, where algorithms for efficient and noise-resistant information coding are used. For example, when using low-speed noise-resistant coding, the operation of long-term accumulation of energy of weak signals is relatively easily implemented using digital signal processing algorithms and methods. Digital signal processing algorithms make it possible to reduce the energy, time, and frequency costs of transmitting signals and images in comparison with the transmission of analog ones. Most of the traditional processing systems operate on an input signal and obtain another output signal. An important class of digital signal processing problems concerns their interpretation. The purpose of such problems is not to obtain an output signal, but to describe the characteristics of the input signal. From the results obtained, it can be seen that in practical cases it is possible to estimate the methodological error based on the amplitude and phase parameters of the measured signal. It forms the basis of the engineering methodology for designing the considered systems. Thus, it can be seen from the experiments that the Butterworth filter is an effective rectifier filter. This means that as a result of corrective filtering, the signal-to-noise ratio is significantly reduced and the signal is cleaned of noise. The determination of the number of digital measurements of the integral parameters of signals and the error arising during the conversion are analyzed. For this purpose, theoretical studies and experiments were carried out in the MATLAB software environment and positive results were obtained.