Recursive Least Squares Estimation (RLS) Algorithm

Efficient implementation for system identification using Recursive Least Squares (RLS) estimation. This algorithm is crucial for determining model order and parameter values. The program implements RLS to compute model order estimates and relevant parameter values with adaptive weight updates.

Design of One-Dimensional Wiener Filter

Implementation of a one-dimensional Wiener filter design approach. The methodology involves generating three sets of observation data, estimating their AR model parameters using methods like the Yule-Walker equations or Burg's algorithm, and analyzing the impact of signal length and model order on experimental results through performance metrics such as mean square error.