Power Spectrum Estimation of the Welch Method Based on Imagery EEG

Li Zhao; Yang He

doi:10.4028/www.scientific.net/AMM.278-280.1260

Paper Titles

Disturbance Attenuating Control for Cellular Neural Networks with Time-Varying Delays
p.1242

Stability Analyses of Neural Networks with Unbounded Time-Varying Delays and Nonlinear Perturbations
p.1247

Research of the Terminal Timer System Based on High-Speed Color Linear CCD
p.1251

Improved GA-NFS-Based Decision Rule Acquisition in Route Selection for Public Transport Line
p.1255

Power Spectrum Estimation of the Welch Method Based on Imagery EEG
p.1260

The Training Method of General Regression Neural Network for GDOP Approximation
p.1265

Water Resources Optimal Allocation Based on Multi-Objective Differential Evolution Algorithm
p.1271

3D Face Recognition in the Conception of Sparse Representation
p.1275

A Beach Image Detection Method Based on Erotic Image Detection
p.1282

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 278-280Power Spectrum Estimation of the Welch Method...

Power Spectrum Estimation of the Welch Method Based on Imagery EEG

Abstract:

Welch method is a direct evolution from the periodogram method. Periodogram method is also commonly used in the power spectrum estimation, there are some inherent shortcomings in periodogram method, such as the variance and resolution of the spectrum estimation is not good, it does not satisfy the consistency estimation conditions and so on, so this paper uses improved periodogram method (welch method) to estimate the motor imagery EEG power spectrum, with Matlab for tools, through the simulation on the experimental data, comparativing and analysising the welch method’s different spectrum estimation properties with different window functions, which provides the theoretical guidance for selecting a suitable window function and makes the welch method play a good role in the EEG feature extraction.