نتایج جستجو برای: pca analysis

تعداد نتایج: 2832621  

2008
John Novembre Matthew Stephens

Nearly 30 years ago, Cavalli-Sforza et al. pioneered the use of principal component analysis (PCA) in population genetics and used PCA to produce maps summarizing human genetic variation across continental regions1. They interpreted gradient and wave patterns in these maps as signatures of specific migration events1–3. These interpretations have been controversial4–7, but influential8, and the ...

Journal: :Asian Pacific journal of cancer prevention : APJCP 2014
Cheng-Xiao Zhao Ming Liu Yong Xu Kuo Yang Dong Wei Xiao-Hong Shi Fan Yang Yao-Guang Zhang Xin Wang Si-Ying Liang Fan Zhao Yu-Rong Zhang Na-Na Wang Xin Chen Liang Sun Xiao-Quan Zhu Hui-Ping Yuan Ling Zhu Yi-Ge Yang Lei Tang Hai-Yan Jiao Zheng-Hao Huo Jian-Ye Wang Ze Yang

BACKGROUND Evidence supporting an association between the 8q24 rs4242382-A polymorphism and prostate cancer (PCa) risk has been reported in North American and Europe populations, though data from Asian populations remain limited. We therefore investigated this association by clinical detection in China, and meta-analysis in Asian, Caucasian and African-American populations. MATERIALS AND METH...

2006
Zong Min WANG Qing Fu FANG Bing ZHOU Qin LI

The large volume of images used in Distance Learning System are required to be compressed in a good ratio to release the storage loading of computer servers. A new image coding Scheme based on Principle Components Analysis (PCA) and Wavelet decomposition is proposed in this paper. Our algorithm includes 1) Principle Components Analysis (PCA)to reduce the information redundancies along temporal ...

Journal: :Optics letters 2011
J Vargas J Antonio Quiroga T Belenguer

We recently presented a new asynchronous demodulation method for phase-sampling interferometry. The method is based in the principal component analysis (PCA) technique. In the former work, the PCA method was derived heuristically. In this work, we present an in-depth analysis of the PCA demodulation method.

2012
Dipika Bansal Krishna Undela Sanjay D'Cruz Fabrizio Schifano

BACKGROUND Emerging evidence suggests that statins may decrease the risk of cancers. However, available evidence on prostate cancer (PCa) is conflicting. We therefore examined the association between statin use and risk of PCa by conducting a detailed meta-analysis of all observational studies published regarding this subject. METHODS Literature search in PubMed database was undertaken throug...

2014
Samarjeet Powalkar

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...

2014
Yanqiong Liu Jun-Qiang Chen Li Xie Jian Wang Taijie Li Yu He Yong Gao Xue Qin Shan Li

BACKGROUND It has been postulated that non-steroidal anti-inflammatory drugs (NSAIDs) use leads to decreased prostate cancer (PCa) risk. In recent years, NSAIDs' role in PCa development has been extensively studied; however, there is not yet a definitive answer. Moreover, the epidemiological results for NSAIDs' effect on PCa-specific mortality have been inconsistent. Therefore, we performed a m...

Journal: :Neural networks : the official journal of the International Neural Network Society 2003
Zhiyong Liu Kai Chun Chiu Lei Xu

The two traditional tasks of object detection and star/galaxy classification in astronomy can be automated by neural networks because the nature of the problems is that of pattern recognition. A typical existing system can be further improved by using one of the local Principal Component Analysis (PCA) models. Our analysis in the context of object detection and star/galaxy classification reveal...

2015
Huishuai Zhang Yi Zhou Yingbin Liang

We investigate the robust PCA problem of decomposing an observed matrix into the sum of a low-rank and a sparse error matrices via convex programming Principal Component Pursuit (PCP). In contrast to previous studies that assume the support of the error matrix is generated by uniform Bernoulli sampling, we allow non-uniform sampling, i.e., entries of the low-rank matrix are corrupted by errors ...

2006
Amit C. Kale R. Aravind

Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are well known techniques for face recognition. Both PCA and LDA by themselves have good recognition rates. We propose Canonical Correlation Analysis (CCA) for combining two feature extractors to improve the performance of the system, by obtaining the advantages of both. CCA finds the transformation for each extractor dat...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید