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An Efficient Use of Principal Component Analysis in Workload Characterization-A Study

Jyotirmoy Sarkar1Snehanshu Saha2Surbhi Agrawal2

1. BITS PILANI & Tech Mahindra2. CBIMMC & Dept.of Computer Science and Engineering,PESIT-BSC

摘要:PCA is a useful statistical technique that has found application in fields such as face recognition,image compression,dimensionality reduction,Computer System performance analysis etc.It is a common technique for finding patterns in data of high dimension.In this paper,we present the basic idea of principal component analysis as a general approach that extends to various popular data analysis techniques.We state the mathematical theory behind PCA and focus on monitoring system performance using the PCA algorithm.Next,an Eigen value-Eigenvector dynamics is elaborated which aims to reduce the computational cost of the experiment.The Mathematical theory is explored and validated.For the purpose of illustration we present the algorithmic implementation details and numerical examples over real time and synthetic datasets.
会议名称:

2014 AASRI Conference on Sports Engineering and Computer Science(SECS 2014)

会议时间:

2014-06-21

会议地点:

London, UK

  • 专辑:

    电子技术及信息科学

  • 专题:

    计算机软件及计算机应用

  • 分类号:

    TP391.41

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