Explore MATLAB source code curated for "峭度" with clean implementations, documentation, and examples.
This experimental program computes various parameters of vibration signals, implementing key statistical and signal processing calculations including mean value, standard deviation, variance, skewness, kurtosis, peak-to-peak value, root mean square amplitude, average amplitude, peak value, waveform factor, crest factor, impulse factor, and margin indicator using efficient numerical algorithms.
A kurtosis-based blind source separation algorithm implementation featuring comprehensive data visualization subroutines for signal analysis.
This paper details an independent component analysis algorithm utilizing kurtosis maximization, featuring comprehensive explanations of each procedural step's function and significance, along with implementation insights for computational efficiency.
This algorithm addresses blind source separation of linearly mixed signals when source probability density functions and activation functions are challenging to determine - particularly when signals contain both super-Gaussian and sub-Gaussian components. By utilizing kurtosis as a statistical measure of signal PDFs, the method adaptively configures activation functions through a switching mechanism, implementing an effective kurtosis-based blind separation approach with robust mixed-signal handling capabilities.
This program provides straightforward feature extraction capabilities for data analysis, implementing key time-domain and frequency-domain features including waveform factor, kurtosis, and frequency band energy percentage with clean, reusable code structure.