Explore MATLAB source code curated for "脑电信号处理" with clean implementations, documentation, and examples.
Implementation of EEG spectrum and power spectrum calculation with visualization. Core methodologies include wavelet transform, wavelet coefficient reconstruction, and computation of power spectra across frequency bands, with code-level explanations of signal processing algorithms.
MATLAB source code for EEG signal acquisition and processing, featuring extraction algorithms for brainwave analysis and cognitive research applications.
Wavelet transform is applied to EEG signal processing for effective time-frequency analysis, extracting valuable information through multi-resolution decomposition algorithms.
MATLAB-based source code featuring two-column EEG data processing, implementation of nonlinear feature extraction algorithms (Renyi entropy, wavelet entropy, LZC complexity), and topographical brain mapping visualization tools
The integration of Independent Component Analysis with Principal Component Analysis is highly suitable for EEG signal processing, implementing techniques for signal decomposition and dimensionality reduction.