structs2

2FSK是利用数字基带信号控制在波的频率来传送信息。经过调制后的2FSK数字信号通过两个频率不同的带通滤波器f1、f2滤出不需要的信号，然后再将这两种经过滤波的信号分别通过包络检波器检波，最后将两种信号同时输入到抽样判决器同时外加抽样脉冲，最后解调出来的信号就是调制前的输入信号。(gudi hduidf hdag sdd w)

time difference of arrival

语音信号处理的端点检测程序，在编程中调用，很实用，值得你一看。(Endpoint detection)

本文详细介绍了16QAM调制方式的算法和理论(a good document for understand the theory and algorithm of 16QAM )

malab有限差分应用,应用于有限差分方程计算。(finite different method.)

INTHIS WE ARE ABLE TO SUMMARIZE fourier analysis application in fingerprint

无刷直流电机的建模和仿真，包含matlab里面的例子，可以仿真成功，有最后的转矩波形(Brushless DC motor modeling and simulation, including inside matlab example, can emulate the success, there is a final torque waveform)

包括svpwm的MATLAB仿真实现的matlab程序和word文本文档说明建立过程(Including svpwm the MATLAB simulation of matlab program and word description of the process of establishing a text document )

对瑞利信道进行仿真，得到清晰的瑞利分布。(For Rayleigh channel simulation, get a clear Rayleigh distribution.)

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.)