Blind signal separation using an adaptive weibull distribution
نویسنده
چکیده
We propose an independent component analysis (ICA) algorithm which can separate mixtures of suband superGaussian source signals with self-adaptive nonlinearities. The ICA algorithem in the framework of natural Riemannian gradient is derived using the parameterized Weibull density model. The nonlinear function in ICA algorithem is self-adaptive and is controlled by the shape parameter of Weibull density model. Computer simulation results confirm the validity and high performance of the proposed algorithm
منابع مشابه
Optimization Neural Network for Blind Signal Separation Using an Adaptive Weibull Distribution
Annotation: In this papre We propose a neural network optimization algorithm for independent component analysis(ICA) which can separate mixtures of suband superGaussian source signals with self-adaptive nonlinearities. The ICA algorithem in the framework of natural Riemannian gradient, is derived using the parameterized Weibull density model. The nonlinear function in ICA algorithem is self-ada...
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 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 کاملFitting the Three-parameter Weibull Distribution by using Greedy Randomized Adaptive Search Procedure
The Weibull distribution is widely employed in several areas of engineering because it is an extremely flexible distribution with different shapes. Moreover, it can include characteristics of several other distributions. However, successful usage of Weibull distribution depends on estimation accuracy for three parameters of scale, shape and location. This issue shifts the attentions to the requ...
متن کاملBlind image separation based on exponentiated transmuted Weibull distribution
In recent years the processing of blind image separation has been investigated. As a result, a number of feature extraction algorithms for direct application of such image structures have been developed. For example, separation of mixed fingerprints found in any crime scene, in which a mixture of two or more fingerprints may be obtained, for identification, we have to separate them. In this pap...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009