Independent Component Analysis (ICA) using the Method of Convolution Mixture in the Intelligent Telecommunication Systems (COMINT) by MATLAB Software

摘要

Modulation recognition is the main part of Smart Telecom receptors and to detect thetype of signal, eliminating the interference, noise and measuring the spectrum is veryuseful and important. The received signals due to a variety of reasons including fadingand multi-alignment phenomena and …. are not very safe and must initially beseparated and process of separation and noise eliminating to be done. For this purpose,signal separation is very important and separation of considered signal from thereceived signals has a great importance in the signal processing ; That one of its bestapplications is the elimination of telecommunication signal interference, noiseelimination from the received signals and speech signals or image or informationseparation from solitary data and, etc … Due to the extensive applications and itsenormous importance, rapidly new and efficient algorithms were introduced in order toprocess and design them. Despite the exiting independence condition, the issue of initialresources derivation from the several signal production sources independent from eachother is possible that we knew it by the name of blind signal separation. The main ideain all signal separation algorithms is the same and is the finding a criterion formeasurement of a density function's non-Gaussian. This criterion must be simple andmeanwhile be resistant to the solitary data and noises. In this paper IndependentComponent Analysis is investigated using the method of Convolution Mixture in theintelligent telecommunication systems (Comint) and finally will be investigated viaMATLAB.