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...

A non-blind color image watermarking scheme using principle component analysis, discrete wavelet transform and singular value decomposition is proposed. The color components are uncorrelated using principle component analysis. The watermark is embedded into the singular values of discrete wavelet transformed sub-band associated with principle component containing most of the color information. ...

this paper presents a deterministic approach for performance assessment of different province’s road safety level at iran. a data envelopment analysis (dea) model considering undesirable input and output indices and a multivariate statistical method, principle component analysis (pca) are used in this paper, while previous studies do not use composite pca-dea method and undesirable input and ou...