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该程序实现了基于小波模极大值，阈值去噪算法，并比较了各种方法的去噪效果。(The program achieved a de-noising based on wavelet modulus maxima algorithm, and effectively removes the signal in Gaussian white noise.)

1.median_filter (功能:使用中值濾波器去除雜訊) 2.mean_filter (功能:使用平均濾波器去除雜訊) 3.fl_stein (功能:使用誤差擴散法,將影像量化和混色) 4.Central_limit (功能:畫圖並證明中央極限定理) (1.median_filter (function: use median filter to remove noise) 2.mean_filter (function: using the average filter to remove noise) 3.fl_stein (function: using the error diffusion method, the image quantification and blending) 4. Central_limit (function: drawing and prove the central limit theorem))

This program contains the explicit descriptions of load forecasting by the Mathworks web site and is very complete. the users can easily apply their own data to it and use the methods to forecast Load and price.

KUAN FILTER FOR NOISE REMOVAL

Sheffield大学开发的matlab工具箱，内含实例。并附有《MATLAB遗传算法工具箱及应用》（西安电子科技大学出版社）对此工具箱及matlab7.0自带的GADS工具箱有详细介绍。(A matlab toolbox developed by Sheffield University, containing examples. Together with an introduction(Xidian University Press).)

应用SIMO技术来构造高矩阵，达到进行盲信道估计技术所需要的条件，（OFDM）(SIMO technology applications to construct high-matrix, reaching for blind channel estimation techniques required conditions, (OFDM))

Author: Xianju Wang Summary: 2 Dimensional Spectral Estimation MATLAB Release: R12 Description: Estimating the power spectrum associated with a random process is desirable in many applications. This package includes four important 2-D spectral estimation methods.(Periodogram, Autorrelation Method, Covariance Method, Modified Covariance Method).(Author : Xianju Wang Summary : 2 Dimensional Spectral Estimation MATLAB Rele ase : R12 Description : Estimating the power spectrum associated with a random process is desirable in many applicati ons. This package includes four important 2-D's pectral estimation methods. (Periodogram. Autorrelation Method, Covariance Method. Modified Covariance Method).)

this document a list of mathemtical forms

matlab基本信号处理函数及实例应用，非常有用的！(matlab basic signal processing functions and application examples, very useful!)

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