Abstract
Comparative evaluations of the frequency responses (FR) of two types of filters implemented by the classical and neural network methods are carried out. It is shown that the neural network principle of the implementation of digital filters can serve as an alternative to the classical method for specifically defined parameters of FR in the pass bands and attenuation bands of the frequencies of signal spectrum. The simplest method for calculating the parameters of the filters’ difference equations is the neural network approach, regardless of the type of classification of discrete and digital filters. The implementation of TM (transmultiplexer) on a digital element base requires the use of methods of filtering, modulating and demodulating signals that are largely different from traditional analog methods. The frequency responses of non-recursive types of filters presented in the paper are based on the property of the approximable function determined only in the pass bands and attenuation bands of the frequencies of signal spectrum.
Highlights
Since the 1970s, the ideas and methods of digital signal processing in radio engineering and telecommunications are receiving increasing attention
The frequency response of the filter is expressed through the ratio of the signal power at the filter output to the signal power at the filter input
If the neural network filter coefficients are calculated when learning a neural network in the mode of a recursive scheme, and the filter is implemented as a non-recursive one, as a result of decreasing the values of parameters of the function F (W, C), the frequency response in the pass band is usually reduced [4]
Summary
Since the 1970s, the ideas and methods of digital signal processing in radio engineering and telecommunications are receiving increasing attention. Significant progress has been made in the development of transmultiplexers (TM) - digital devices interfacing communication systems with time and frequency division of channels. Implementation of TM on a digital element base requires the use of digital methods of filtering, modulating and demodulating signals that are largely different from traditional analog methods [1]. Its solution is usually performed by various classical methods, namely: 1) firstly, the filter type is defined, and its transfer function is found; 2) firstly, the transfer function is set, which provides the necessary filtering properties in the frequency range, and the filter is restored from it
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