Who can tell us how the time-frequency analysis algorithm of wavelet transform is realized?

JTFA, as a powerful tool for analyzing time-varying non-stationary signals, has become a hot spot in modern signal processing research. As a new signal processing method, JTFA has attracted more and more attention in recent years. Time-frequency analysis method provides joint distribution information in time domain and frequency domain, and clearly describes the relationship between signal frequency and time.

The basic idea of time-frequency analysis is to design a joint function of time and frequency to describe the energy density or intensity of signals at different frequencies at the same time. This joint function of time and frequency is called time-frequency distribution for short. By analyzing the signal with time-frequency distribution, the instantaneous frequency and its amplitude at each moment can be given, which can be used for time-frequency filtering and time-varying signal research.

2 The importance of time-frequency analysis of signals

(1) Time and frequency are the two most important physical quantities to describe signals.

(2) The time domain and frequency domain of signals are closely related.

Main methods of signal time-frequency analysis

(1) window Fourier transform (Gabor transform);

(2) continuous wavelet transform;

(3) Wigner-Weil distribution;

(4) Hilbert-Huang Transform (HHT); ;