Morlet Wavelet Transform for Wavelet Ridge Extraction

This text demonstrates how Morlet wavelet transform can be employed to extract wavelet ridges, which subsequently enables the implementation of 2FSK demodulation. The implementation typically involves calculating the continuous wavelet transform using a complex Morlet wavelet as the mother wavelet, followed by ridge detection algorithms that track local maxima in the time-frequency plane. Through this methodology, we can achieve more accurate signal demodulation, yielding more reliable results. Additionally, other wavelet transform algorithms can be utilized to further optimize the demodulation process, such as wavelet packet transform or discrete wavelet transform. By employing these different wavelet transform algorithms, we can compare their performance differences in demodulation applications and select the most suitable algorithm for specific requirements. Furthermore, we can explore how wavelet transforms can be applied to other signal processing tasks, including signal denoising and feature extraction. The implementation of signal denoising often involves thresholding techniques on wavelet coefficients, while feature extraction may utilize energy distribution analysis across different frequency bands. Through continuous research and exploration of wavelet transform applications, we can expand our knowledge and skills while achieving more accomplishments across various domains.