信号 Resources

Showing items tagged with "信号"

This algorithm represents the classic Maximum Likelihood Estimation method for SNR estimation, which leverages the prior probability density function of the received channel to achieve accurate signal-to-noise ratio measurements. The ML approach demonstrates robust performance in estimating SNR through statistical optimization techniques, typically implemented via numerical methods like gradient ascent or expectation-maximization algorithms.

MATLAB 383 views Tagged
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Generate a continuous signal containing low, medium, and high frequency components, perform sampling and spectral analysis, design three types of filters (high-pass, low-pass, band-pass) for signal filtering, and observe the frequency spectrum of filtered signals with implementation guidance using signal processing libraries.

MATLAB 236 views Tagged
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In partial discharge testing, acquired signals often contain white noise and periodic interference that need removal. This implementation utilizes the commonly used db6 wavelet from the Daubechies series to perform a 9-level multiresolution decomposition. Based on the energy characteristics of white noise, threshold values for each scale are estimated using hard thresholding processing, followed by signal reconstruction. The algorithm involves wavelet decomposition, noise variance estimation, and threshold application using MATLAB's wdenoise function or custom implementation with wthresh.

MATLAB 189 views Tagged
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Performing signal spectrum analysis using FFT (Fast Fourier Transform) in digital signal processing applications including implementation approaches and key algorithmic considerations.

MATLAB 241 views Tagged
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