The Power Spectrum Estimation of the AR Model Based on Motor Imagery EEG

2013 ◽  
Vol 706-708 ◽  
pp. 1923-1927 ◽  
Author(s):  
Li Zhao ◽  
Yang He
Keyword(s):  
Power Spectrum ◽  
Motor Imagery ◽  
Ar Model ◽  
Spectrum Estimation ◽  
Power Spectrum Estimation ◽  
Estimation Algorithms ◽  
Model Based

This paper uses three common AR model power spectrum estimation algorithms which are the Yule-Walker method, the burg method and the improved covariance method. Taking Matlab as a tool, the corresponding algorithms are used to carry out the power spectrum estimation of motor imagery EEG, the relationships and distinctions between the spectrum charts are compared in order to find the relatively appropriate algorithm for analyzing the EEG, which aims at providing a theoretical guidance for processing the motor imagery EEG and laying a foundation for further research.

AR Model Power Spectrum Estimation and MATLAB Simulation

2014 ◽  
Vol 971-973 ◽  
pp. 1561-1564 ◽  
Author(s):  
Min Ji ◽  
Jing Feng He ◽  
You Qiang Lai
Keyword(s):  
Parameter Estimation ◽  
Power Spectrum ◽  
Frequency Domain ◽  
Ar Model ◽  
Model Parameters ◽  
Spectrum Estimation ◽  
Actual Situation ◽  
Matlab Simulation ◽  
Power Spectrum Estimation ◽  
Advantages And Disadvantages

the power spectrum estimation researches various characteristics of signals in the frequency domain. The purpose is that signals are recognized and extract .Because these useful signals are submerged in noise .The article introduces estimation in the classic power spectrum and modern power spectrum. It is important that algorithm of AR model parameters are introduced in the parameter estimation of several typical. It discusses the advantages and disadvantages of various algorithms, and with the help of MATLAB platform, the various algorithms of power spectrum are simulated, in order to undertake choosing according to the actual situation.

scholarly journals The Auto-Regressive Model and Spectrum Information Entropy Judgment Method for High Intensity Focused Ultrasound Echo Signal

2021 ◽  
Vol 11 (20) ◽  
pp. 9558
Author(s):  
Shang-Qu Yan ◽  
Zheng Huang ◽  
Bei Liu ◽  
Xu-Sheng Ni ◽  
Han Zhang ◽  
...  
Keyword(s):  
Power Spectrum ◽  
Information Entropy ◽  
Focused Ultrasound ◽  
Estimation Method ◽  
High Intensity Focused Ultrasound ◽  
Ar Model ◽  
Spectrum Estimation ◽  
Echo Signal ◽  
Power Spectrum Estimation ◽  
Auto Regressive

For accurate evaluation of high intensity focused ultrasound (HIFU) treatment effect, it is of great importance to effectively judge whether the sampled signal is the HIFU echo signal or the noise signal. In this paper, a judgment method based on an auto-regressive (AR) model and spectrum information entropy is proposed. In total, 188 groups of data are obtained while the HIFU source is on or off through experiments, and these sampled signals are judged by this method. The judgment results of this method are compared with empirical judgments. It is found that when the segment number for the power spectrum estimated by AR model is 14 to 17, the judgment results of this method have a higher consistency with empirical judgments, and Accuracy, Sensitivity and Specificity all have good values. Moreover, after comparing and analyzing this method with the classic power spectrum estimation method, it is found that the recognition rate of the two sampled signals of this method is higher than that of the classic power spectrum estimation method. Therefore, this method can effectively judge the different types of sampled signals.

Power Spectrum Estimation of the Welch Method Based on Imagery EEG

2013 ◽  
Vol 278-280 ◽  
pp. 1260-1264 ◽  
Author(s):  
Li Zhao ◽  
Yang He
Keyword(s):  
Experimental Data ◽  
Feature Extraction ◽  
Power Spectrum ◽  
Motor Imagery ◽  
Spectrum Estimation ◽  
Power Spectrum Estimation ◽  
Eeg Power Spectrum ◽  
Window Functions ◽  
Welch Method ◽  
Eeg Power

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.

The Simulation of Burg Algorithm for AR Model Power Spectrum Estimation

2011 ◽  
Vol 179-180 ◽  
pp. 426-430
Author(s):  
Hong He ◽  
Xing Huang ◽  
Fang Liu ◽  
Da Jian Zhang ◽  
Ming Feng Hou
Keyword(s):  
Power Spectrum ◽  
Direct Method ◽  
Spectral Estimation ◽  
Ar Model ◽  
Spectrum Estimation ◽  
Matlab Simulation ◽  
Transform Method ◽  
Power Spectrum Estimation ◽  
Fast Fourier Transform Method ◽  
Spectrum Curve

Classical spectral estimation, whether the direct method or indirect method, are available to fast Fourier transform method, their concepts are clear and easy to understand, its resolution is proportional to . This paper describes the commonly used in modern power spectrum estimation based on AR model Burg algorithm, MATLAB simulation shows this method to estimate the power spectrum curve, results showed that the Burg algorithm in spectral resolution and model in the order of sub-option square than the self-correlation algorithm has obvious advantages.

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