Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Feature extraction from terahertz pulses for classification of RNA data via support vector machines|
|Citation:||Micro- and Nanotechnology: Materials, Processes, Packaging, and Systems III, Jung-Chih Chiao, Andrew S. Dzurak, Chennupati Jagadish, David V. Thiel (eds.), pp. 641516 1-10|
|Series/Report no.:||Proceedings of SPIE--the International Society for Optical Engineering ; 6415.|
|Conference Name:||Smart Materials, Nano- & Micro-Smart Systems (2006 : Adelaide, Australia)|
|Xiaoxia Yin, Brian W.-H. Ng, Bernd Fischer, Bradley Ferguson, Samuel P. Mickan, and Derek Abbott|
|Abstract:||This study investigates binary and multiple classes of classification via support vector machines (SVMs). A couple of groups of two dimensional features are extracted via frequency orientation components, which result in the effective classification of Terahertz (T-ray) pulses for discrimination of RNA data and various powder samples. For each classification task, a pair of extracted feature vectors from the terahertz signals corresponding to each class is viewed as two coordinates and plotted in the same coordinate system. The current classification method extracts specific features from the Fourier spectrum, without applying an extra feature extractor. This method shows that SVMs can employ conventional feature extraction methods for a T-ray classification task. Moreover, we discuss the challenges faced by this method. A pairwise classification method is applied for the multi-class classification of powder samples. Plots of learning vectors assist in understanding the classification task, which exhibit improved clustering, clear learning margins, and least support vectors. This paper highlights the ability to use a small number of features (2D features) for classification via analyzing the frequency spectrum, which greatly reduces the computation complexity in achieving the preferred classification performance.|
|Description:||© 2006 COPYRIGHT SPIE--The International Society for Optical Engineering|
|Appears in Collections:||Electrical and Electronic Engineering publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.