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是两个综合性较强的实例，分别是Visual C++实现的基于神经网络的文字识别系统和车牌定位系统(Are two examples of more integrated, namely Visual C++ implementation of text based on neural networks and the license plate recognition system positioning systems)

说明：  现代普估计的AR模型求解，采用的是周期图法，自己写的程序，菜鸟，谅解(AR model)

分数阶统计是现代统计信号处理的重要内容，这里是alpha、beta分布的情况，仿真程序(Fractional statistics is an important content of modern statistical signal processing, where alpha and beta distribution emulator)

从介绍功率谱的估计的理论基础入手，分析经典谱估计和现代谱估计，以及在Matlab中的实现方法。(Introduced the power spectrum from the estimated theoretical basics, analysis of classic and modern spectral estimation spectral estimation, as well as the realization of Matlab.)

采用不同窗函数对信号进行了WELCH谱估计，并可以做出对比分析。(Different window function of the signal spectrum estimation WELCH, and can make a comparative analysis.)

这是一个利用自相关函数以及中心肖波算法求取基音频率的程序，其基于MATLAB。(it is a program about get pitch.it based on MATLAB)

语音处理源程序，已经过调试，直接运行即可实现(Speech processing source program, have been debug, direct operation can be realized )

频率采样法设计高通FIR滤波器，结实得很详细。MATLAB代码。(MATLAB FIR )

matlab 图形绘制功能，在直角坐标系或极坐标系下绘制二维和三维图形(Matlab graphics functions in the rectangular coordinate system or polar coordinates draw 2 d and 3 d graphics)

Power flow studies, commonly known as load flow, form an important part of power system analysis. They are necessary for planning, economic scheduling and control of an existing system as well as planning its future expansion. The problem consists of determining the magnitudes and phase angle of voltages at each bus and active and reactive power flow in each line. In solving power flow problem, the system is assumed to be operating under balanced conditions and a single-phase model is used. Four quantities are assumed at each bus. These are voltage magnitude v, phase angle  , real power P, and reactive power Q.The Newton Raphson method of load flow analysis is an iterative method which approximates the set of non-linear simultaneous equations to a set of linear simultaneous equations using Taylor’s series expansion and the terms are limited to first order approximation.