In this thesis we introduce and investigate a method combining Principle Component Analysis (PCA) and Independent Component Analysis (ICA) for Blind Source Separation (BSS). A recursive method for the PCA is applied to meet the demands of a real-time application, and for the ICA algorithm, the Information maximization principle is used. In an effort to address convolutive BSS, the separation is...

Non-gaussian component analysis (NGCA) introduced in [24] offered a method for high dimensional data analysis allowing for identifying a low-dimensional non-Gaussian component of the whole distribution in an iterative and structure adaptive way. An important step of the NGCA procedure is identification of the non-Gaussian subspace using Principle Component Analysis (PCA) method. This article pr...

Non-gaussian component analysis (NGCA) introduced in [24] offered a method for high dimensional data analysis allowing for identifying a low-dimensional non-Gaussian component of the whole distribution in an iterative and structure adaptive way. An important step of the NGCA procedure is identification of the non-Gaussian subspace using Principle Component Analysis (PCA) method. This article pr...

multivariate statistical techniques such as cluster analysis, multidimensional scaling and principal component analysis were applied to evaluate the temporal and spatial variations in water quality data set generated for two years (2008-2010) from six monitoring stations of veli-akkulam lake and compared with a regional reference lake vellayani of south india. seasonal variations of 14 differen...

Crop discrimination is still very challenging issue for researcher because of spectral reflectance similarity captured in non-imaging data. The objective this research work to focus on crop challenge. We have used ASD FieldSpec4 Spectroradiometer collection leaf samples four crops Wheat, Jowar, Bajara and Maize. vegetation indices some band featuring our dataset. applied Principle Component Ana...

The quest of providing more secure identification system has led to a rise in developing biometric systems. Dorsal hand vein pattern is an emerging biometric which has attracted the attention of many researchers, of late. Different approaches have been used to extract the vein pattern and match them. In this work, Principle Component Analysis (PCA) which is a method that has been successfully a...

Principle component analysis (PCA) was used to extract components from the solid-state nuclear magnetic resonance (NMR) spectra of bacterial cellulose (BC). Polymers such as cellulose have several domain structures, and their structure and dynamics are reflected in the variety of solid-state spectra derived from different parameters. The complexity of the obtained spectra makes the analysis of ...