TwoStep

这是用MATlab进行用户界面设计的程程序这是界面的功能是：对连续时间函数w(t)=exp(-abs(t))在【-5，5】区间内进行采样，利用样条插值重构该连续函数，绘出重构图形并输出重构误差。(It is used MATlab process of user interface design process which is the interface functions are: a continuous time function w (t) = exp (-abs (t)) in the range】 【-5,5 samples, using spline Reconstruction of the continuous interpolation function, draw the reconstruction graphics and output reconstruction error.)

说明：  给出正弦加噪函数，通过FFT,DTFT,做频谱变化，幅度谱和相位谱。(Sine plus noise function is given by FFT, DTFT, make changes in the spectrum, amplitude spectrum and phase spectrum.)

主要设计了在matlab下异步电动机在dq坐标系下的仿真。(The main design of the asynchronous motor in matlab simulation in the dq coordinate system.)

说明：  自己翻译的一篇最新外文文献《使用无需重建最佳探测器的宽带压缩传感认知无线电》(Own translation of a the latest foreign literature use without having to rebuild the best detectors broadband compressed sensing cognitive radio &quot )

Code to read Midi Files in matlab

matlab做的buck闭环仿真，自己做的，这个是闭环的，加反馈，PID补偿费，用的是增量式PID，连续，稳定(simulation of buck with feenback PID)

格基约减下的zf(迫零检测)算法，适用于多输入多输出系统(lattice reduction aided ZF algorithms)

环境下构建一种新的系统辨识仿真工具箱(SIST: System Identification Toolbox)的原理与实现,讨论了在MATLAB 环境下工具箱的数据和算法结构形式,以及利用GUIDE完成图行界面的设计,用MATLAB 与C++混编技术实现物理系统的I/O 接口和系统辨识... (err)

CSTR产生数据的程序。由于CSTR具有广泛的应用性，故特地利用伪随机序列激发CSTR系统，产生数据。(CSTR generate data procedures. As CSTR with extensive application, it specifically using pseudo-random sequence inspired CSTR systems to generate data.)

这篇文章是盲信号处理，因为是英文文章，所以大家看内容就好了。(Principal component analysis (PCA) is a mainstay of modern data analysis- a black box that is widely used but poorly understood. The goal of this paper is to dispel the magic behind this black box. This tutorial focuses on building a solid intuition for how and why principal component analysis works furthermore, it crystallizes this knowledge by deriving from simple intuitions, the mathematics behind PCA . This tutorial does not shy away from explaining the ideas informally, nor does it shy away from the mathematics. The hope is that by addressing both aspects, readers of all levels will be able to gain a better understanding of PCA as well as the when, the how and the why of applying this technique.)