With the rapid development of the computer technology, people may have to deal with more and more information every day, which even can be described as mass information. Cluster analysis technique which is a very useful tool in processing information and one of the most important methods in data mining, has become a hot issue
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Blind source separation is a process of recovering each individual original signal from a number of mixed-signals. Blind speech signal processing is the mind problem of blind source separation. In this paper, three kinds of blind speech signal processing models including normal, underdetermined and over determined are studied as follow:First, a blind separation algorithm PCA-ICA
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Blind source separation is a process of recovering each individual original signal from a number of mixed-signals. Blind speech signal processing is the mind problem of blind source separation. In this paper, three kinds of blind speech signal processing models including normal, underdetermined and over determined are studied as follow:First, a blind separation algorithm PCA-ICA
(Read More…)
Blind source separation is a process of recovering each individual original signal from a number of mixed-signals. Blind speech signal processing is the mind problem of blind source separation. In this paper, three kinds of blind speech signal processing models including normal, underdetermined and over determined are studied as follow:First, a blind separation algorithm PCA-ICA
(Read More…)
The main purpose of image segmentation is to extract the interesting regions from thebackground for further analysis. Image segmentation techniques have been widely used inmedical image processing, pattern recognition, computer vision and other fields. For theimages are ambiguous and uncertain inherently, image segmentation is a classic problem inimage processing. Many scholars have done a lot
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The main purpose of the medical image segmentation is to distinguish between different objects in a given and to label each pixel with its underlying class. Image segmentation is very important to image preprocessing and patter recognition, such as feature quantification, image registration 3D reconstruction and etc. In this thesis, the brain magnetic resonance (MR)
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The main purpose of the medical image segmentation is to distinguish between different objects in a given and to label each pixel with its underlying class. Image segmentation is very important to image preprocessing and patter recognition, such as feature quantification, image registration 3D reconstruction and etc. In this thesis, the brain magnetic resonance (MR)
(Read More…)
For fault diagnosis of complex system, intelligent information processing technology is current hot spot and inevitable tendency to development of fault diagnosis. The methods of fault diagnosis combined by FCM and SVM are studied and analysed in this paper.This paper mainly studies and discusses on the following aspects:First, fuzzy clusting analysis is one of important
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The main purpose of the medical image segmentation is to distinguish between different objects in a given and to label each pixel with its underlying class. Image segmentation is very important to image preprocessing and patter recognition, such as feature quantification, image registration 3D reconstruction and etc. In this thesis, the brain magnetic resonance (MR)
(Read More…)
For fault diagnosis of complex system, intelligent information processing technology is current hot spot and inevitable tendency to development of fault diagnosis. The methods of fault diagnosis combined by FCM and SVM are studied and analysed in this paper.This paper mainly studies and discusses on the following aspects:First, fuzzy clusting analysis is one of important
(Read More…)
