For Single input Single output (SISO), the least squares method is used to identify the parameters of the system. Least squares parameter estimation is a classic method, concept is concise, wide adaptation, derived from the regression analysis of mathematical statistics, it can provide a minimum variance sense the best fitting model with the experimental data, in some cases, the statistics can be obtained with the maximum likelihood method is as good effect, and can easily establish relations with other identification algorithm. Under certain conditions, the least square parameter estimation method has the best statistical properties, namely consistent, unbiased and effective results. This code mainly USES the method of recursive least squares identification method and the augmented least squares identification method to identify the model parameters, using gaussian noise as the noise of the system.

code\RELS.m
code\RLS.m
code

• 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．