Wavelet Power Spectral Domain Functional Principal Component Analysis for Feature Extraction of Epileptic EEGs

A New Palm-Print Image Feature Extraction Method Based on Wavelet Transform and Principal Component Analysis

In recent years, as one of the biometric identification technology, palm-print identification has received many reseachers’ attention. To solve the key problem of palm-print recognition -feature extraction, we propose a new method, which based on wavelet transform and principal component analysis. In general, we use wavelet transform to deal with palm print images and extract high-dimensional w...

Comparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition

Background: Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impac...

Wavelet based Watermarking Techniques using Principal Component Analysis Domain

With increasing use of internet and effortless copying, tempering and distribution of digital data, copyright protection for multimedia data has become an important issue. Digital watermarking emerged as a tool for protecting the multimedia data from copyright infringement. In digital watermarking an imperceptible signal "mark" is embedded into the host image, which uniquely identifie...

Feature Extraction Using Genetic Algorithm Based Principal Component Analysis

Feature reduction of hyperspectral images: Discriminant analysis and the first principal component

When the number of training samples is limited, feature reduction plays an important role in classification of hyperspectral images. In this paper, we propose a supervised feature extraction method based on discriminant analysis (DA) which uses the first principal component (PC1) to weight the scatter matrices. The proposed method, called DA-PC1, copes with the small sample size problem and has...