Wigner distribution decomposition and cross-term deleted representation
Signal Processing
Time-frequency analysis: theory and applications
Time-frequency analysis: theory and applications
Time-frequency representation based on the reassigned S-method
Signal Processing
Time-frequency signal analysis based on the windowed fractional Fourier transform
Signal Processing - Special issue: Fractional signal processing and applications
Image Processing - Principles and Applications
Image Processing - Principles and Applications
Training a Support Vector Machine in the Primal
Neural Computation
An efficient algorithm to extract components of a composite signal
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Kernel design for reduced interference distributions
IEEE Transactions on Signal Processing
A signal-dependent time-frequency representation: optimal kerneldesign
IEEE Transactions on Signal Processing
A method for time-frequency analysis
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Elimination of interference terms of the discrete Wignerdistribution using nonlinear filtering
IEEE Transactions on Signal Processing
International Journal of Data Analysis Techniques and Strategies
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An efficient method based on 2D signal processing techniques and fractional Fourier transform is presented to suppress interference terms of Wigner distribution (WD). The proposed technique computes Gabor transform (GT) of a multi-component signal to obtain a blurred time-frequency (t-f) image. Signal components in GT image are segmented using connected component segmentation and are filtered out using precise application of fractional Fourier transform. A crisp t-f representation is then obtained by computing the sum of products of WD and GT of the isolated signal components. The efficacy of the proposed technique is demonstrated using examples of synthetic signals and real-life bat signals. Proposed scheme gives satisfactory performance even when cross-terms of WD overlap auto-terms and computational cost analysis shows that it is more efficient than recent interference suppression techniques of comparable performance. Moreover, the proposed technique does not require any prior info regarding the nature of signal.