Step-motor

说明：  用MATLAB编的 谱估计里的伯格算法 效果很好(Made use of MATLAB in the Burg spectral estimation algorithm works well)

MATLAB implementation of 4 different diffusion filtering algorithms. Better performance to remove noise than conventional low-pass filtering.

模型预测控制，动态矩阵控制的程序以及其改进，分享给大家，以供参考(Model predictive control, dynamic matrix control procedure and its improvement, to share to us, for your reference)

本代码是将改进的果蝇算法运用于scaffer函数，显示该算法的性能。(fruit fly algorithm used in scaffer function。)

power system economics

use for photovoltanic power converter

matlab的牛顿插值和样条插值多项式，以及牛顿插值和样条插值的误差。(matlab Newton polynomial interpolation and spline interpolation, and Newton interpolation and spline interpolation errors.)

用MATLAB语言根据成形滤波器法实现通信环境中的瑞利信道的仿真(Realization of Rayleigh channel communication environment using MATLAB simulation language based on shape filter)

OFDM发射和接收收机，包括QAM、信道估计和S&C同步算法。(OFDM receiver and transmitter，include QAM modulation ，channel estimation and S&C synchronization algorithm。)

This file compares three different versions of the Kalman filter. The Kalman filter is used for recursive parameter estimation. The Kalman filter can handle noisy measurements. The first implemented filter (fcn_KF) is the Kalman filter with standard update of the covariance matrix P. The covariance matrix reflects the uncertainties of the predictions. To improve the numerical stability Potter developed a square root update (fcn_KF_SRP) of the covariance matrix P. Another version is the square root covariance update via triangularization (fcn_KF_SRT). This file generates a model. Then the three Kalman filters perform an estimation of the model parameter. At the end the results are compared. Sources: Simon, D. (2006): Optimal state estimation Kaminski, P. (1971): Discrete Square Root Filtering: A Survey of Current Techniques Golub, G. (1996): Matrix Computations