Open access peer-reviewed chapter

Time-Frequency Based Feature Extraction for Non-Stationary Signal Classification

By Luis David Avendaño-Valencia, Carlos Daniel Acosta-Medina and Germán Castellanos-Domínguez

Submitted: November 1st 2010Reviewed: April 11th 2011Published: August 23rd 2011

DOI: 10.5772/19101

Downloaded: 3370

© 2011 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike-3.0 License, which permits use, distribution and reproduction for non-commercial purposes, provided the original is properly cited and derivative works building on this content are distributed under the same license.

How to cite and reference

Link to this chapter Copy to clipboard

Cite this chapter Copy to clipboard

Luis David Avendaño-Valencia, Carlos Daniel Acosta-Medina and Germán Castellanos-Domínguez (August 23rd 2011). Time-Frequency Based Feature Extraction for Non-Stationary Signal Classification, Applied Biomedical Engineering Gaetano D. Gargiulo and Alistair McEwan, IntechOpen, DOI: 10.5772/19101. Available from:

Embed this chapter on your site Copy to clipboard

<iframe src="http://www.intechopen.com/embed/applied-biomedical-engineering/time-frequency-based-feature-extraction-for-non-stationary-signal-classification" />

Embed this code snippet in the HTML of your website to show this chapter

chapter statistics

3370total chapter downloads

More statistics for editors and authors

Login to your personal dashboard for more detailed statistics on your publications.

Access personal reporting

Related Content

This Book

Next chapter

Classification of Emotional Stress Using Brain Activity

By Seyyed Abed Hosseini and Mohammad Bagher Naghibi-Sistani

Related Book

First chapter

Spatial Unmasking of Speech Based on Near-Field Distance Cues

By Craig Jin, Virginia Best, Gaven Lin and Simon Carlile

We are IntechOpen, the world's leading publisher of Open Access books. Built by scientists, for scientists. Our readership spans scientists, professors, researchers, librarians, and students, as well as business professionals. We share our knowledge and peer-reveiwed research papers with libraries, scientific and engineering societies, and also work with corporate R&D departments and government entities.

+3,550 Open Access Books

+57,400 Citations in Web of Science

+108,500 IntechOpen Authors and Academic Editors

+560,000 Unique visitors per month

More about us