نتایج جستجو برای: pca method

تعداد نتایج: 1647441  

Journal: :IOP Conference Series: Earth and Environmental Science 2021

Journal: :Int. J. Machine Learning & Cybernetics 2013
Alok Sharma Kuldip K. Paliwal Seiya Imoto Satoru Miyano

In this paper we present QR based principal component analysis (PCA) method. Similar to the singular value decomposition (SVD) based PCA method this method is numerically stable. We have carried out analytical comparison as well as numerical comparison (on Matlab software) to investigate the performance (in terms of computational complexity) of our method. The computational complexity of SVD ba...

2016
Ramesh Kumar Vimal Chand

The selection of appropriate wavelets is an important target for any application. In this paper Face recognition has been performed using Principal component analysis (PCA), Gaussian based PCA and Gabor based PCA. PCA extracts the relevant information from complex data sets and provides a solution to reduce dimensionality. PCA is based on Euclidean distance calculation which is minimized by app...

2015
H. R. Shahdoosti H. Ghassemian

1. Ph.D. Student, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran, [email protected] 2. Professor, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran, [email protected] Abstract An ideal fusion method preserves the spectral information in fused image without spatial distortion. The PCA is believ...

2014
Zhigang Feng

To effectively diagnose the deterministic faults of a LPRE ground-testing bed, the fault diagnosis method based on PCA and SOM is proposed. The dimension reduction process of PCA not only reduces data size, but also reduces noise influence. It also implements a visualization of fault status identification and fault variable orientation by SOM. Simulation and real fault data results indicate tha...

Journal: :Pattern Recognition Letters 2007
Alok Sharma Kuldip K. Paliwal

In this paper we present an efficient way of computing principal component analysis (PCA). The algorithm finds the desired number of leading eigenvectors with a computational cost that is much less than that from the eigenvalue decomposition (EVD) based PCA method. The mean squared error generated by the proposed method is very similar to the EVD based PCA method. 2007 Elsevier B.V. All rights ...

1994
Horst Bischof Kurt Hornik

This paper presents a new method for image compression by neural networks. First, we show that we can use neural networks in a pyramidal framework, yielding the so-called PCA pyramids. Then we present an image compression method based on the PCA pyramid, which is similar to the Laplace pyramid and wavelet transform. Some experimental results with real images are reported. Finally, we present a ...

2007
Bin Zhu Lu Jiang Yaguang Luo Yang Tao

Automated inspection of apple quality involves computer recognition of good apples and blemished apples based on geometric or statistical features derived from apple images. This paper introduces a Gabor feature-based kernel principal component analysis (PCA) method by combining Gabor wavelet representation of apple images and the kernel PCA method for apple quality inspection using near-infrar...

Journal: :Entropy 2015
Shunfang Wang Ping Liu

The classic principal components analysis (PCA), kernel PCA (KPCA) and linear discriminant analysis (LDA) feature extraction methods evaluate the importance of components according to their covariance contribution, not considering the entropy contribution, which is important supplementary information for the covariance. To further improve the covariance-based methods such as PCA (or KPCA), this...

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