MATLAB Implementation of Morlet Algorithm for Wavelet Signal Processing

MATLAB Implementation of Morlet Algorithm for Wavelet Signal Processing

In wavelet signal processing, the Morlet algorithm serves as a fundamental method for signal analysis and processing. This algorithm employs wavelet transform techniques using the Morlet wavelet as the basis function to extract signal characteristics by analyzing time-frequency properties. In MATLAB implementation, key functions include wavelet transform functions (such as cwt for continuous wavelet transform), FFT functions for fast Fourier transformation, and custom Morlet wavelet generation. The algorithm involves parameters like center frequency and bandwidth control, typically implemented through Gaussian-windowed complex sinusoids. Programming implementation requires careful parameter tuning for different signal types, including time-frequency resolution adjustment and scale parameter optimization. By developing appropriate MATLAB scripts, researchers can perform detailed signal processing and analysis across various applications, obtaining comprehensive time-frequency representations. The implementation typically involves wavelet coefficient computation, inverse transformations, and feature extraction procedures.

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