A Modified Method for Blind Source Separation
نویسندگان
چکیده
Blind source separation is an important but highly challenging technology in astronomy, physics, chemistry, life science, medical science, earth science, and applied sciences. Independent Component Analysis (ICA) employed technologies in applied computer science for blind source separation. In the separation of blind sources under multiple sensors, it can estimate approximately the types of signal. This study proposed a modified ICA algorithm which can estimate the actual phase and amplitude and retrieve the signals separated by blind source separation to its original state. This method has great potential for application in many different fields. Key-Words: Computer Science; Blind Source Separation; Independent Component Analysis
منابع مشابه
Research of Blind Signals Separation with Genetic Algorithm and Particle Swarm Optimization Based on Mutual Information
Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...
متن کاملBlind Separation of Jointly Stationary Correlated Sources
The separation of unobserved sources from mixed observed data is a fundamental signal processing problem. Most of the proposed techniques for solving this problem rely on independence or at least uncorrelation assumption for source signals. This paper introduces a technique for cases that source signals are correlated with each other. The method uses Wold decomposition principle for extracting ...
متن کاملResearch of Blind Signals Separation with Genetic Algorithm and Particle Swarm Optimization Based on Mutual Information
Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...
متن کاملCalculation of Leakage in Water Supply Network Based on Blind Source Separation Theory
The economic and environmental losses due to serious leakage in the urban water supply network have increased the effort to control the water leakage. However, current methods for leakage estimation are inaccurate leading to the development of ineffective leakage controls. Therefore, this study proposes a method based on the blind source separation theory (BSS) to calculate the leakage of water...
متن کاملBlind Signal Separation Using an Extended Infomax Algorithm
The Infomax algorithm is a popular method in blind source separation problem. In this article an extension of the Infomax algorithm is proposed that is able to separate mixed signals with any sub- or super-Gaussian distributions. This ability is the results of using two different nonlinear functions and new coefficients in the learning rule. In this paper we show how we can use the distribution...
متن کامل