MATLAB Wavelet Analysis Implementation for Vibration Signal Processing
A wavelet analysis program for vibration signal analysis featuring practical implementation with MATLAB's Wavelet Toolbox functions
Wavelet Packet Analysis for Extracting Characteristic Frequencies from Vibration Signals
Wavelet Packet Analysis for extracting characteristic frequencies from vibration signals, combined with energy spectrum analysis calculations, including implementation approaches using signal processing toolboxes
MATLAB Wavelet Analysis for Bearing Fault Vibration Signals
A MATLAB wavelet analysis program for bearing fault vibration signals, capable of extracting fault characteristic frequencies using multi-resolution analysis and time-frequency decomposition techniques.
Image Compression Based on Wavelet Transform and MATLAB Implementation
Wavelet analysis represents a sophisticated branch of signal processing where wavelet transforms enable critical applications including image compression, vibration signal decomposition and reconstruction. Compared to Fourier transforms, wavelet transformations operate as local transforms in both spatial and frequency domains, allowing efficient information extraction from signals. Through fundamental operations like scaling and translation, wavelet transforms achieve multi-scale signal decomposition and reconstruction, effectively overcoming many limitations of Fourier analysis. As a new mathematical discipline, wavelet analysis synthesizes functional analysis, Fourier analysis, and numerical analysis, serving as a powerful "time-scale" analysis and multi-resolution analysis technique with extensive applications across signal processing, speech synthesis, image compression, and pattern recognition.
Analysis of ITD Method with Implementation Insights
Analysis of the Intrinsic Time-scale Decomposition Method and Its Code Implementation Considerations