Implementation of Levinson-Durbin Algorithm Using MATLAB

Function Description: MATLAB implementation of the Levinson-Durbin algorithm for autoregressive (AR) model parameter estimation. The algorithm efficiently computes AR coefficients through recursive solution of the Yule-Walker equations using backward prediction errors and reflection coefficients. Function Name: Levinson_Durbin_Algo. Input Parameters: (1) R: autocorrelation matrix or its estimate, (2) P: order of the AR model. Output Parameters: (1) A: row vector of length P+1 containing AR model parameters, (2) E: noise power (prediction error variance). Calling Functions: none. Called By: L_D_sim.m. Author: mingcheng. Creation Date: 2009-11-13. Modification Date: 2009-11-13. Version: V1.0.

Classical Power Spectrum Estimation and Adaptive Equalization Algorithms

1. This folder contains all programs for two experiments: classical power spectrum estimation and adaptive equalization algorithms. 2. R.m, LMS.m, and LMSmain.m are programs for adaptive equalization algorithms: R.m computes the autocorrelation matrix and eigenvalues of input signals; LMS.m implements the time-domain LMS algorithm using statistical methods to simulate learning curves under same channel parameters and different step sizes; LMSmain.m is the main experimental program that generates results and curves based on specific data requirements. 3. functionx.m, fzhouqitu.m, spectrum.m, bt.m, bart_lett.m, welch.m, and SPECTRUMmain.m are programs for classical spectrum estimation.