Dissertation > Excellent graduate degree dissertation topics show

EEG based on compressed sensing compressive sampling

Author: ZhouWei
Tutor: WeiZhiHui
School: Nanjing University of Technology and Engineering
Course: Pattern Recognition and Intelligent Systems
Keywords: Compressed sensing Multi-channel EEG Joint Sparse Compressive sampling
CLC: TN911.7
Type: Master's thesis
Year: 2011
Downloads: 281
Quote: 0
Read: Download Dissertation

Abstract


In this paper, based on compressive sensing EEG compressive sampling , first studied the single-channel EEG compression based on compressive sensing sampling , and then based on the improvement in the single-channel multi-channel joint compression algorithm sampling . In medical practice , usually a long period of several multi-channel EEG measurement repeatability , it will produce large amounts of data . How to effectively deal with these data is a serious problem . Compressed sensing theory emerged in recent years as an effective solution to this problem proposed a new solution ideas . In view of this , the paper first introduces the basics of EEG signals and compressed sensing priori theoretical framework . The next study based on compressed sensing theory of compressive sampling single-channel EEG signals , including EEG best sparse decomposition , experimental comparison, the EEG signals , a Gaussian function , Gaussian wavelet function, Mexican hat function as the atomic generating function constructed redundant dictionary , you can achieve better EEG signal sparse decomposition effect ; measurement matrix choice experiments comparing the commonly used measurement matrix for reconstruction errors, such as Gaussian random matrices , Toeplitz matrix , etc., next, use the measurement matrix for sparse decomposition coefficients were observed vector values ??are measured compressive sampling completed , and finally by these measurements using an orthogonal matching pursuit algorithm recovers the coefficient vector , and then complete the reconstruction of the original EEG signals . In the single-channel EEG signals compressive sampling , based on the EEG signals of each channel in view of the link between the proposed multi-channel EEG signals joint compressive sampling , saving the sparse decomposition used in atomic number and the number of observations , to achieve a more efficient compression sampling .

Related Dissertations

  1. Facial expression recognition based on sparse representation residuals fusion,TP391.41
  2. Research on Cooperative Spectrum Sensing Schemes Based on Random Matrix Theory and Compressed Sensing,TN925
  3. Research on the Applications of Compressed Sensing in Wireless Sensor Network,TN929.5
  4. The Key Technologies of Distributed Compressed Sensing in Wireless Sensor Networks,TN929.5
  5. A Research on Channel Estimation Based on Compressed Sensing for Broadband Wireless Communications,TN92
  6. Research of Distributed Video Coding Based on Compressed Sensing,TN919.81
  7. Research on Compressed Sensing and the Application in UWB Channel Estimation,TN925
  8. Research on Modeling Technique of Speech Signal Based on Compressed Sensing,TN912.3
  9. Based on sparse representation Face Image Recognition Method,TP391.41
  10. Multiscale information fusion algorithm,TP202
  11. Stepped frequency SAR super-resolution imaging technology,TN957.52
  12. Visible and infrared image fusion algorithm,TP391.41
  13. Infant Pain Facial ExpressioN Recogintion Based on Compressive Sensing,TP391.41
  14. Research on Compressed Sensing and Its Application in IR-UWB,TN925
  15. Based on Contourlet transform digital watermark embedding algorithm optimization and performance analysis,TP309.7
  16. The Research of Speech Coding Based on Compressed Sensing,TN912.3
  17. Research on Spectrum Detection Technology from Compressed Sensing,TN925
  18. Research on Signal Reconstruction Algorithm of Compressive Sense,TN911.6
  19. Compressed Sensing Based Abnormal Events Detection in Wireless Communication Net-works,TN929.5
  20. Study on Image Recontrution of Compressed Sensing Based on the Dual Tree Complex Wavelet,TP391.41

CLC: > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Communication theory > Signal processing
© 2012 www.DissertationTopic.Net  Mobile