fullbridge_pid

该书一本很好的MATLAB仿真教程,特别适合初学者,也可以作为专业人员的参考书(Book is a very good tutorial MATLAB simulation, especially for beginners, but also can serve as a professional reference books)

SC-FDMA中信道编码性能研究，付费论文。。。(SC-FDMA Performance of Channel Coding, paid papers. . .)

全部信息熵的计算，包括信息熵，条件信息熵以及信息增益。附带Andrew的信息增益教程(All information entropy calculations, including information entropy, conditional entropy and information gain. Andrew incidental information gain Tutorials)

本文对基于非线性控制方法的倒立摆系统控制进行了系统的研究(In this paper, control methods based on nonlinear inverted pendulum control system research)

眼睛图像虹膜区域提取，内附简单说明。采用粗精双重定位。(iris recognize)

说明：  fir滤波器具体参数： 带通范围：0.35pi－0.8pi，1dB 阻带为<0.2pi,>0.8pi,60dB(fir filter specific parameters : Bandpass Scope : 0.35pi- 0.8pi, resistance bands 1dB)

说明：  一种MGA方法(Contourlet变换)程序包，相信对从事基于图像表示理论方面的朋友一定有用！(A kind of MGA method (Contourlet transform) package, I believe in the theory of image-based friends that must be useful!)

基于支持回归向量机的端点延拓程序解决EMD端点效应，包括向左延拓和向后延拓。(EMD solve end effect based on support vector machine regression endpoint extension programs, including the left rear extension and extension.)

Compressive sampling is an emerging technique that promises to effectively recover a sparse signal from far fewer measurements than its dimension. The compressive sampling theory assures almost an exact recovery of a sparse signal if the signal is sensed randomly where the number of the measurements taken is proportional to the sparsity level and a log factor of the signal dimension. Encouraged by this emerging technique, this thesis briefly reviews the application of Compressive sampling in speech processing. It comprises the basic study of two necessary condition of compressive sensing theory: sparsity and incoherence. In this thesis, various sparsity domain and sensing matrix for speech signal and different pairs that satisfy incoherence condition has been compiled.

分数阶系统建模和控制的经典教材，深入浅出的讲述了相关知识(The classic textbook of modeling and control of fractional order system gives a brief account of relevant knowledge.)