Method for extracting zgv features based on local entropy reconstruction-optimized multi-synchrosqueezing transform algorithm

A method for extracting ZGV features based on a local entropy reconstruction-optimized multi-synchrosqueezing transform algorithm, wherein the method is implemented through the following steps:

• S1:
• a computer acquires a to-be-processed signal with time-varying features and performs a short-time Fourier transform on the to-be-processed signal to obtain a preliminary short-time Fourier transform result;
• S2:
• based on the short-time Fourier transform result from the step S1, the computer estimates an instantaneous frequency corresponding to the short-time Fourier transform result;
• S3:
• the computer inputs the instantaneous frequency estimated in the step S2 and the short-time Fourier transform result from the step S1 into a synchrosqueezing transform process, and performs time-squeezing reassignment to obtain a synchrosqueezing transform result;
• S4:
• the computer performs iterative processing on the synchrosqueezing transform result from the step S3 until a preset convergence condition is met, and outputs a final iteration result;
• S5:
• the computer performs Renyi entropy calculation and reconstruction accuracy calculation respectively on the final iteration result from the step S4 to obtain a Renyi entropy value and reconstruction accuracy for evaluating the transform result;
• S6:
• the computer constructs a Bayesian cost function using the Renyi entropy value and reconstruction accuracy from the step S5, and performs Bayesian optimization on the Bayesian cost function to obtain a globally optimized window function length;
• and
• S7:
• the computer applies the globally optimized window function length from the step S6 to a Gaussian window function to generate a new Gaussian window function, re-executes the short-time Fourier transform on the original signal with the time-varying features using the new window function, and outputs a time-frequency image of the ZGV features.