Computer and Information Science » Numerical Analysis and Scientific Computing

Principal Component Analysis

Edited by Parinya Sanguansat, ISBN 978-953-51-0195-6, Hard cover, 300 pages, Publisher: InTech, Chapters published March 02, 2012 under CC BY 3.0 license
DOI: 10.5772/2340

This book is aimed at raising awareness of researchers, scientists and engineers on the benefits of Principal Component Analysis (PCA) in data analysis. In this book, the reader will find the applications of PCA in fields such as image processing, biometric, face recognition and speech processing. It also includes the core concepts and the state-of-the-art methods in data analysis and feature extraction.

Dr. Parinya Sanguansat

Panyapiwat Institute of Management, Thailand

Parinya Sanguansat received the B.Eng., M.Eng and Ph.D. degrees from Chulalongkorn University, Thailand, in 2001, 2004 and 2007, respectively. He is currently a Lecturer at Faculty of Engineering and Technology, Panyapiwat Institute of Management, Thailand . His research interests include machine learning, pattern recognition and image processing.

Fields of Research

Experience

Education

  • Engineering, Chulalongkorn University, Bangkok

    2004 – 2007

    Electrical Engineering

Editorials

  • Principal Component Analysis - Multidisciplinary Applications
    Principal Component Analysis - Multidisciplinary Applications

    This book is aimed at raising awareness of researchers, scientists and engineers on the benefits of Principal Component Analysis (PCA) in data analysis. In this book, the reader will find the applications of PCA in fields such as taxonomy, biology, pharmacy,finance, agriculture, ecology, health and architecture.

  • Principal Component Analysis
    Principal Component Analysis

    This book is aimed at raising awareness of researchers, scientists and engineers on the benefits of Principal Component Analysis (PCA) in data analysis. In this book, the reader will find the applications of PCA in fields such as image processing, biometric, face recognition and speech processing. It also includes the core concepts and the state-of-the-art methods in data analysis and feature extraction.

  • Principal Component Analysis - Engineering Applications
    Principal Component Analysis - Engineering Applications

    This book is aimed at raising awareness of researchers, scientists and engineers on the benefits of Principal Component Analysis (PCA) in data analysis. In this book, the reader will find the applications of PCA in fields such as energy, multi-sensor data fusion, materials science, gas chromatographic analysis, ecology, video and image processing, agriculture, color coating, climate and automatic target recognition.

Publications