weisuiji

matlab实现的FSK调制解调程序，请大家使用，并提出建议。谢谢(matlab implementation of the FSK modulation and demodulation process, let us use, and make recommendations. Thank you)

Huang 98 文章——The empirical mode decomposition and the hilbert spectrum(Huang 98 articles- The empirical mode decomposition and the hilbert spectrum)

balanis antenna code part5

使用Matlab的M文件编写的数控三轴直线运动代码，为验证DSP上的算法而编(Matlab M-file used to prepare three-axis linear motion of the CNC code, in order to verify the algorithm and the DSP for)

对excel中出现的多组缺失且混乱的数据做插值，节省excel手工调整、分组插值的时间，提供效率，参数可以根据用户需要自行调整。(To excel in the multiple sets of missing and disorder data interpolation, save excel manual adjustment, grouping interpolation of time, provide efficiency.)

ICA程序，1996提出的ica算法Basic ICA code in MATLAB (as used in Bell and Sejnowski 1996).(Basic ICA code)

产生火炮发射炮弹的航迹，模型的建立，并画出仿真结果。(The track artillery shells fired generation, model, and draw the simulation results.)

Simulink Coder™ (formerly Real-Time Workshop® ) generates and executes C and C++ code from Simulink® diagrams, Stateflow® charts, and MATLAB® functions. The generated source code can be used for real-time and nonreal-time applications, including simulation acceleration, rapid prototyping, and hardware-in-the-loop testing. You can tune and monitor the generated code using Simulink or run and interact with the code outside MATLAB and Simulink.

文章在IEEE上发表，一种崭新的支持矢量机SVM源码(article published in IEEE, a new support vector machine SVM FOSS)

MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。(MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of view, the signal processing can be decomposed observation space the signal subspace and the noise subspace, it is clear that the two spaces are orthogonal. Signal Subspace data received by the array covariance matrix and eigenvectors corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector components.)