We propose an Iterative Nonlinear Gaussianization Algorithm (INGA) which seeks a nonlinear map from a set of dependent random variables to independent Gaussian random variables. A direct motivation of INGA is to extend principal component analysis (PCA), which transforms a set of correlated random variables into uncorrelated (independent up to second order) random variables, and Independent Com...

Image blurring process is commonly formulated as two-dimensional convolution between the latent image and the blurring system. Blind image restoration problem is to estimate the latent image only from the blurred image. Conventional blind image restoration techniques tend to solve this problem by estimating the blurring system and therefore their effectiveness are dependent to the accuracy of t...

abstract many researchers have recently considered the use of data obtained from remote sensing (r.s) to reveal changes. in the present study, we have attempted to reveal the morphodynamic changes in taleghan river basin through image satellite and by analyzing the principal component analysis (pca) and fuzzy logic. the final map indicates the intensity of changes through, 15-years interval obs...

As the word become moving towards the globalization in engineering techniques, the capacity and techniques establish an identity of individuals using face as a biometric has become a more important. This paper includes the face recognition using the Extended Principal Component Analysis (EPCA) algorithm. The proposed algorithm uses the concept of PCA and represents an extended version of PCA by...

Principal component analysis (PCA) (also called Karhunen Loève transform) has been widely used for dimensionality reduction, denoising, feature selection, subspace detection and other purposes. However, traditional PCA minimizes the sum of squared errors and suffers from both outliers and large feature noises. The L1-norm based PCA (more precisely L1,1 norm) is more robust. Yet, the optimizatio...

Principal component analysis (PCA) is an effective tool for spectral decorrelation of hyperspectral imagery, and PCA-based spectral transforms have been employed successfully in conjunction with JPEG2000 for hyperspectral-image compression. However, the computational cost of determining the data-dependent PCA transform is high due to its traditional eigendecomposition implementation which requi...

Now a day’s Facial Expression Recognition field is growing and playing important role in communication. Facial expression recognition is a prototype where both humans and computer underperforms. It has great significance for the classification of video based management and video retrieval. It may be using in behaviour science and psychologist. There are many methods which is used to recognized ...

This article analyses processes of change undergone by Spanish medium-sized cities during 1981–2011 on the one hand, and 2000–2018 other, as they are different sources. We established a classification to show importance this type city starting from hypothesis that process is generalised in which behave according their position territory. The dynamics predominantly associated with contexts econo...