Abstract
This paper presents the methodology, properties and processing of the time-frequency techniques for non-stationary signals, which are frequently used in biomedical, communication and image processing fields. Two classes of time-frequency analysis techniques are chosen for this study. One is short-time Fourier Transform (STFT) technique from linear time-frequency analysis and the other is the Wigner-Ville Distribution (WVD) from Quadratic time-frequency analysis technique. Algorithms for both these techniques are developed and implemented on non-stationary signals for spectrum analysis. The results of this study revealed that the WVD and its classes are most suitable for time-frequency analysis.
Highlights
IntroductionMost of the signals are non-stationary and time-varying signals. Further, the classical and modern methods are widely used to process the stationary signals in which they transform the signals from time-domain to frequency-domain and vice versa
In nature, most of the signals are non-stationary and time-varying signals
The results of this study revealed that the time-frequency resolution of the short-time Fourier Transform (STFT) technique is inversely related to the window length
Summary
Most of the signals are non-stationary and time-varying signals. Further, the classical and modern methods are widely used to process the stationary signals in which they transform the signals from time-domain to frequency-domain and vice versa. Many signals of biological origin are varying in a random manner called non-stationary signals and are changing their properties over the length of the analysis time. In order to process such non-stationary signals, time-frequency analysis and processing methods are required. They fall into one of the two categories of time-frequency distributions (TFDs), the linear time-frequency distributions and the quadratic time-frequency distributions (QTFDs). Two types of time-frequency representation techniques are considered; Linear Time frequency distribution and quadratic time frequency distribution and their principle properties are investigated. The realization of this distribution for hardware and software platforms requires a discrete version. Algorithms were developed for discrete time-frequency STFT and WVD techniques and were tested on non-stationary signals for joint time-frequency analysis
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
