Advanced Time-Frequency Analysis Software with WVD and Pseudo-WVD Algorithms

The advanced time-frequency analysis software provides robust implementations of Wigner-Ville Distribution (WVD) and multiple pseudo-WVD algorithms, including kernel function optimizations for cross-term suppression. The software is required to execute example programs from Hu Guangshu's "Modern Signal Processing Tutorial," which demonstrates key time-frequency analysis techniques through practical MATLAB-based implementations. Featuring efficient signal preprocessing capabilities, the software incorporates digital filtering algorithms (FIR/IIR design), wavelet denoising methods, and signal amplification routines with customizable parameters. The preprocessing module includes adaptive thresholding algorithms for noise reduction and signal normalization functions. Supporting multiple data formats (MAT, CSV, WAV, TXT), the software implements flexible import/export handlers with data validation checks and format conversion utilities. This facilitates seamless data interchange and collaboration across different platforms and research environments. Whether for academic research, engineering applications, or educational purposes, the software delivers powerful analytical capabilities through its optimized time-frequency transforms (including STFT and Cohen's class distributions), batch processing functionality, and visualization tools with interactive parameter adjustment interfaces.