Smoothed Pseudo Wigner-Ville Distribution

This article discusses the implementation of the Smoothed Pseudo Wigner-Ville Distribution (SPWVD) algorithm. The SPWVD is a time-frequency analysis method designed to characterize the time-varying spectral properties of non-stationary signals. The core algorithm involves computing weighted averages of both time-domain and frequency-domain signal representations to generate a joint time-frequency distribution. From an implementation perspective, the SPWVD typically requires: - Separate smoothing windows for time and frequency dimensions - Computational optimization using FFT-based kernel calculations - Parameter tuning for window lengths to balance time-frequency resolution This method can process various signal types including audio, image, and video signals, making it widely applicable in fields such as signal processing, communications engineering, and biomedical engineering. The implementation often involves matrix operations for the double convolution process and careful handling of boundary effects in finite-length signals.