Hop sparse Bayesian learning ( SBL ) and compressible sensing theory ( CS ) , give a compressible image reconstruction in the noise measurement conditions . The method of the CS theory image reconstruction process as a linear regression problem , the image to be reconstructed is unknown weighting parameters of the regression model towel SBL method to determine the weights given a priori probability distribution to limit the complexity of the model and the introduction of the hyper-parameters

Image reconstruction method based on sparse Bayesian learning.pdf

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．