STATCOM_DIY

说明：  一个很好的MIMO的信道模型程序，很实用。 没有密码，可以自由下载(A very good MIMO channel model program, it is practical. No password, you can free download)

说明：  支持向量机回归在股市预测中的应用,有论文和大量仿真曲线说明(the application of SVR in the Stock prediction)

说明：  关于livsvm工具箱的一个扩展工具箱，比原来的要多了几种函数(An extension of the toolbox on the livsvm toolbox, to be more than the original function of several)

说明：  车牌识别程序，结合C++和MATLAB语言编写。在雨天、或光线不足时保持高识别率。(License plate recognition program, combined with C++ and MATLAB language. In the rain, or light enough to maintain a high recognition rate.)

深度学习中自动编码器，对象为手写体识别应用，希望可以一同研究学习(Deep Learning AutoEncoder)

对于初学者具有参考意义，相控阵天线的方向图（切比雪夫加权），包含位置式PID算法、积分分离式PID，实现了对10个数字音的识别程序利用matlab GUI实现的串口编程例子，验证可用。(For beginners with a reference value, Phased array antenna pattern (Chebyshev weights), It contains positional PID algorithm, integral separate PID, Realization of 10 digital audio recognition program Use serial programming examples matlab GUI implementation, Verification is available.)

Short Term Energy is important for filtering a signal. With Short Term Energy, we can get voiced and unvoiced.

说明：   在高阶谱分析工具箱是一个M文件集合实施了多种先进的信号处理算法的频谱估计，polyspectral估计，时频分布计算，并包含许多实际应用如时延估计，谐波恢复，参数估计的Volterra（非线性）模型，以及自适应线性预测。其他潜在的应用包括音响，生物医学，经济学，地震勘探，无损检测，海洋学，等离子体物理，雷达，声纳，语音等(The Higher-Order Spectral Analysis Toolbox is a collection of M-files that implement a variety of advanced signal processing algorithms for spectral estimation, polyspectral estimation, and computation of time-frequency distributions, with applications such as time delay estimation, harmonic retrieval, parameter estimation of Volterra (nonlinear) models, and adaptive linear prediction. Other potential applications include acoustics, biomedicine, econometrics, exploration seismology, nondestructive testing, oceanography, plasma physics, radar, sonar, speech etc. )

This is a matlab simulation for CPM which is using viterbi decoder to decode the signal. There is pulse shaping used in this file and the default signal is assumed to be rectangukar

C# code for software engineer and student who want to learn