Designation and simulating the ML algorithm using the natural gradient in order to Independent Component Analysis (ICA) in the intelligent telecommunication systems (COMINT) using the ADS2008 software
Journal Title: Journal of Science and today’s world - Year 2013, Vol 2, Issue 4
Abstract
Diagnosing the modulation is the main part of telecommunication intelligent receivers and to identify the signal type, interference removal, noise and measurement is very useful, the received signals are not very confident because of many reasons including the multi-path and fading phenomena. and must be separate first and the separation and noise removal to be done.For this purpose , the signal separation is very important , the regarding signal 's separation from received signal , is very important in the process of signal that from is best applications is to remove the interference from the telecommunication signals , removal of noise of data and speech signals or images and separation of data from far data and etc,.. Due to its wide applications and its vary importance, many new and useful algorithms to process and designing them were presented. With the existence of independence condition, the issue of extracting the initial references from several source of independent signal creation is possible that we know it as the signal blind separation. The main idea in all algorithms of signal is the same and is as the finding a criteria for measurement of non-guassian of a density function. These criteria must be simple as well as to be resistant to the noises and solitary data. In this paper the separation of signals was done via ML algorithm using the natural gradient and linear estimation will be reviewed and finally the results from simulation will be reviewed via ADS 2008.
Authors and Affiliations
Gohar Varamini , Ahmad Rohani, Mehdi Nikkhah
Keywords
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