Explore MATLAB source code curated for "近似熵" with clean implementations, documentation, and examples.
Entropy (including Approximate Entropy and Sample Entropy) concepts explained for beginners. Comprehensive coverage of theoretical foundations and practical code implementation approaches.
Multiscale entropy can be used to measure the complexity of time series, offering improved performance compared to approximate entropy and sample entropy through multi-scale decomposition analysis.
MATLAB-implemented programs for computing approximate entropy, enhanced sample entropy, and optimized fuzzy entropy—serving as robust complexity metrics for algorithm analysis with embedded pattern matching and fuzzy set operations.
This is my university graduation project titled "Noise Analysis Using Harmonic Wavelet Transform Combined with Approximate Entropy" which I hope will be useful for researchers and practitioners in signal processing.
A MATLAB program for calculating approximate entropy, designed specifically for EEG signal analysis. This implementation provides a computational framework to quantify signal complexity and extract meaningful patterns from brainwave data. The code serves as a reference implementation and includes parameter configurations for window size and delay time optimization. Users are encouraged to provide feedback for potential improvements.
Methods for calculating approximate entropy in EEG signals or time series data with algorithm implementations and code considerations