runs Kalman-Bucy filter over observations matrix Z for 1-step prediction onto matrix X (X can = Z) with model order p V = initial covariance of observation sequence noise returns model parameter estimation sequence A, sequence of predicted outcomes y_pred and error matrix Ey (reshaped) for y and Ea for a along with inovation prob P = P(y_t | D_t-1) = evidence

kalman
......\gaussres.m
......\kf.m
......\kfdemo.m
......\kfdemo.mat
......\normalis.m
......\read_me.txt
......\waitbar.m

• 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．