PIDcalc

说明：  仿真通过利用虚拟信道模型而产生瑞利衰落信道(rayleigh)

基于傅里叶变换的matlab下的二维周期性光子晶体带隙的计算绘图程序，属于冷门资料，网上很少见。(Based on Fourier transform matlab under the two-dimensional periodic photonic bandgap calculation drawing program, belonging to popular information, online rare.)

Robert Lafore-Object Oriented Programmining

实现对激光自混合干涉的仿真，对各个参数的仿真都可以实现。但性能不是很好。(Laser self-mixing interference simulation, simulation of the various parameters can be achieved. But the performance is not very good.)

SEP protocol in matlab for wireless sensor networks

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：  QC-LDPC基矩阵H的构建方法及MATLAB实现，具有详细解释(Various encoding and decoding methods of LDPC)

The MATLAB function generates series of time correlated samples with rayleigh distribution.

用matlab设计的一个蜂窝拓扑的程序，开发环境matlab(Design with matlab topology of a cellular process, development environment matlab)

本书内容沿用了《数字图像处理》一书的组织方式。采用这种方法，读者很容易理解 本书讨论的所有数字图像处理概念，并将它们作为进一步阅读的最新参考。所选的软件工具来自MATLAB 数字图像处理工具箱，该工具箱在教育和工业应用中同样占有优势。(The book follows the organization of Digital Image Processing, a book. With this method, the reader is easy to understand. All digital image processing concept discussed in this book, and use them as a reference for further reading the latest. The selected software tools MATLAB digital image processing toolbox, the toolbox in education and industrial applications take advantage of the same.)