lorenz

说明：  实现短时傅里叶变换，并动态显示傅里叶变换的过程(Achieve short time Fourier transform and Fourier transform the process of dynamic display)

PMSM table for driver for PMSM motor

该程序是Weickert提出的结构张量扩散去噪模型。(The program corresponds to the structure tensor diffusion denoising model which is proposed by Weickert )

通过MATLAB的SIMULINK模型设计，实现可控正弦信号发生器，并通过DSP BUILDER中的SIGNAL COMPILER转换成QuartusII工程，并实现硬件的下载。(Through the MATLAB SIMULINK model design, realization controllable sine SIGNAL generator, and through the DSP BUILDER of SIGNAL COMPILER converted into QuartusII engineering, and realize the hardware of the download. )

基于OFDMA系统的多用户资源分配算法，论文配备MATLAB代码，入门的好教材。(— Orthogonal Frequency Division Multiple Access (OFDMA) basestations allow multiple users to transmit simultaneously on different subcarriers during the same symbol period. This paper considers basestation allocation of subcarriers and power to each user to maximize the sum of user data rates, subject to constraints on total power, bit error rate, and proportionality among user data rates. Previous allocation methods have been iterative nonlinear methods suitable for ofine optimization. In the special high subchannel SNR case, an iterative root-nding method has linear-time complexity in the number of users and N logN complexity in the number of subchannels. We propose a non-iterative method that is made possible by our relaxation of strict user rate proportionality constraints. Compared to the root-nding method, the proposed method waives the restriction of high subchannel SNR, has signicantly lower complexity, and in simulation, yields higher user data rates.)

实现傅里叶变换高通、低通滤波，理想滤波，各种滤波因子。(Fourier transform to achieve high-pass, low-pass filtering, ideal filtering, filter factor.)

this is matlab program

matlab 实现arnold 图像置乱(matlab arnold)

为sinudoidal模型的AIC阶估计.AIC信息准则即Akaike information criterion，是衡量统计模型拟合优良性的一种标准，又由于它为日本统计学家赤池弘次创立和发展的，因此又称赤池信息量准则。它建立在熵的概念基础上，可以权衡所估计模型的复杂度和此模型拟合数据的优良性。 在一般的情况下，AIC可以表示为： AIC=2k-2ln(L) 其中：k是参数的数量，L是似然函数。 假设条件是模型的误差服从独立正态分布。 让n为观察数，RSS为剩余平方和，那么AIC变为： AIC=2k+nln(RSS/n) 增加自由参数的数目提高了拟合的优良性，AIC鼓励数据拟合的优良性但是尽量避免出现过度拟合(Overfitting)的情况。所以优先考虑的模型应是AIC值最小的那一个。赤池信息准则的方法是寻找可以最好地解释数据但包含最少自由参数的模型。(AIC order estimation for sinudoidal model)

Scource for Induction Motor Scalar Control