Explore MATLAB source code curated for "微弱信号" with clean implementations, documentation, and examples.
MATLAB implementation of Duffing equation for weak signal detection, featuring two methodological approaches: inline function definition and @fan function implementation with parameter optimization capabilities.
MATLAB-based source code for weak signal extraction, detection, and analysis. The implementation first computes key statistical parameters including mean, mean square value, variance, frequency spectrum, and power spectral density of input signals to identify useful signal components. Subsequently, it extracts target signals and calculates their statistical properties (mean, mean square value, variance, probability density) along with spectral characteristics (frequency spectrum and power spectral density), accompanied by visualization of corresponding curves using MATLAB's plotting functions.
Extraction of full autocorrelation coefficients for weak signals and their representation as sample feature vectors, including implementation approaches and algorithm explanations.
MATLAB implementation for detecting weak signal frequencies using Duffing oscillator system, capable of identifying signals within 0.03 frequency deviation from periodic driving force with -68dB SNR tolerance
Simulation of weak signal detection using stochastic resonance principles, including source code implementation of the fourth-order Runge-Kutta algorithm for solving the Langevin equation.