Digital_modulation_FCN

应用RLS自适应算法实现系统逆变识，并画出了系统的学习曲线(system identify using the RLS of adaptive filter)

说明：  利用Matlab软件平台对JTC进行了图像识别仿真实验，得到了二维及三维相关输出图像，显示出尖锐的相关峰。仿真实验表明：联合变换进行图像识别中存在强烈的零级干扰，干扰信号是有用信号的7.14倍，输出结果不理想；采用功率谱相减法可以消除零级强干扰，进而提高了图像的识别能力。(Simulations of joint transform correlator (JTC) using Matlab is implemented, and the 2-D and 3-D drawings of the correlation image are obtained. In the simulation experiments, the sharper correlation peaks are showed. The result shows that strong disturbance of zero rank exists in the simulation of JTC, and it is 7.14 times stronger than the useful signal thus, the power spectrum subtraction is used to eliminate the strong disturbance, and the capacity of image recognition is improved.)

学习多孔介质的好算法。可以放心参考运用,可以运行的(Porous media is a good learning algorithms. You can rest assured reference use, you can run)

MATLAB程序，做阻尼振动的小球的运动作投影，观察在阻尼振动过程中，小球的振幅衰弱情况(MATLAB program, do the damping vibration movement of the ball for the projector, observe the damping vibration process, the weak amplitude of the ball)

APF的模型，采样ip-iq法进行谐波提取，PI控制作为补偿算法，三电平spwm作为调制方式，在网侧添加了LCL滤波，个人感觉效果还不错，准备再添加重复控制，在谐波提取方面采样DFT来尝试(APF model, sampling ip-iq method for harmonic extraction, PI control as compensation algorithms, three-level spwm as modulation, the network side added a LCL filter, the effect of personal feeling good, ready to add a duplicate control, in harmony wavelet extraction areas to try sampling DFT)

matlab simulink implementation and analysis of Three-phase inverter2

说明：  voiceprint声纹识别算法的实现MSR(speaker varification by I-Vector,)

这本Matlab编程是Stephen J. Chapman的经典作品，本上独特的强调自上而下的编程方法，而且在全书中皆有提醒和注意常犯的错误(This is Stephen J. Chapman Matlab programming classics, this emphasis on the unique top-down programming, but also in the book have the sound alerts and attention to common mistakes)

说明：  matlab图像处理源码，共分17章，相当全面(Matlab source image processing, is divided into 17 chapters, is very comprehensive)

Active contour with level set and Kass methods. start with initial circles around objects and then converge in edges of objects, matlab