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一个做中频处理的matlab仿真源程序，通信系统专用(IF processing matlab to do a simulation of the source process)

基于matlab的几种语音信号端点检测方法(Several based on matlab voice signal endpoint detection method)

TM/TE照射无限长导体、介质柱的解析解MATLAB程序(TM/TE light infinitely long conductor, dielectric cylinder analytical solution of the MATLAB program)

Finds the roots of a function using the arc-length method

说明：  通过大主应力和小主应力求解摩擦角和粘聚力(The friction angle and cohesion are solved by large principal stress and small principal stress)

半色调技术对图像进行打印和显示。半色调技术是一种基于点模式的灰度级图像打印方案。在本实验中，给出了用点模式近似表示的10个灰度级(Halftone image printing and display. Half-tone technique is a model based on gray-scale image point of printing solutions. In this experiment, given the dot pattern similar to that of the 10 gray level)

Email parser in C# dotnet

n point fft program which computes the dft of a function using cooley tukey techniques

本文采用小波神经网络进行交通流量预测，短时交通流量存在随机性和非线性因素，影响预测的准确性。传统预测模型难以反映交通流量变化特点，同时传统神经网络易陷入局部极小值，泛化能力差，交通流量预测精度低。为了提高短时交通流量预测精度，提出一种小波神经网络的短时交通流量预测模型。小波神经网络可以对短时交通流量随机性、不确定性进行局部分析，并进行非线性预测，验证了模型的有效性，进行了对比试验。验证结果表明，小波神经网络提高了短时交通流量预精度，预测结果更具应用价值。(In this paper, wavelet neural network is used to forecast traffic flow. There are random and nonlinear factors in short-term traffic flow, affecting the accuracy of prediction. The traditional prediction model is difficult to reflect the characteristics of traffic flow changes. At the same time, the traditional neural network is easy to fall into the local minimum, the generalization ability is poor, and the prediction accuracy of traffic flow is low. In order to improve the accuracy of short-term traffic flow forecasting, a short-term traffic flow prediction model based on wavelet neural network is proposed. The wavelet neural network can analyze the randomness and uncertainty of short-term traffic flow and perform nonlinear prediction. The validity of the model is verified and a comparative experiment is conducted. The verification results show that the wavelet neural network improves the short-term traffic flow pre-precision, and the prediction result has more application value.)

说明：  一种新型自适应信号时频处理方法，特别适用于非线性非平稳信号的分析处理。(A new adaptive signal time-frequency processing method is proposed, which is especially suitable for the analysis and processing of non-linear and non-stationary signals.)