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Discrete Time-Frequency Signal Analysis and Processing Techniques for Non-Stationary Signals

Discrete Time-Frequency Signal Analysis and Processing Techniques for Non-Stationary Signals
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摘要 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. 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.
出处 《Journal of Applied Mathematics and Physics》 2018年第9期1916-1927,共12页 应用数学与应用物理(英文)
关键词 NON-STATIONARY Signal SHORT TERM FOURIER TRANSFORM WIGNER Ville Distribution Algorithm Non-Stationary Signal Short Term Fourier Transform Wigner Ville Distribution Algorithm
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