Using Wavelet Analysis for Signal Processing of Information Transmission Systems

Currently, the use of wavelet analysis makes it possible to solve various problems in the formation and processing of information, perform measurement tasks, and perform compression and regeneration of signals with low distortion. For example, with of wavelet processing it is possible to carry out effective pattern recognition with better performance than with multivariate statistical analysis; for digital information processing systems allows you to develop modern methods and algorithms for signal processing to solve radar and hydroacoustic problems; for infocommunication systems, wavelet analysis allows solving problems of generating, transmitting, receiving and processing information in real time, being a relevant and necessary solution for digital information transmission systems; performing basic algorithms for spectral analysis, filtering and signal synthesis, which allows for more economical use of technical resources; obtain more efficient methods of processing, compression and regeneration of signals transmitted over digital communication channels with low distortion. The article discusses methods of threshold wavelet signal processing using various threshold functions. A subsequent comparative analysis was also carried out for the selected communication signal by determining the risk assessment.