pid

Genrate traffic accourding to defined distribution based on ON-OFF model

多尺度LBP的原代码，用于人脸识别，在orl数据库中的识别率达97 以上。(Multi- scale LBP original code, used in face recognition and the recognition rate of over 97 in orl database.)

主要用于计算目标前向、侧向、后向散射特征，同时完成RCS极坐标图的绘制(Used to calculate the target forward, sideways, backward scattering, and complete the drawing of the polar diagram RCS)

matlab coding forbbo

DTW-语音识别，是在matlab中做的，比较方便快捷了。(DTW-speech recognition, in matlab to do, the more convenient of the.)

huffman coding and huffman decoding

说明：  基于隐马尔可夫过程目标识别的源程序，希望对大家有用，识别效过挺高的。(Target recognition based on hidden Markov process of the source, we want to be useful to identify effective than pricey for.)

The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.

《MATLAB神经网络30个案例分析》中的第11个例子，案例11 连续Hopfield神经网络的优化-旅行商问题优化计算。希望对大家有一定的帮助！(The MATLAB neural network analysis of 30 cases of 11 examples, case 11 continuous Hopfield neural network optimization- traveling salesman problem optimization calculation. Hope to have certain help to everybody! )

滑模控制的一个matlab程序，给出了M文件和SINULINK的仿真，模块用S函数编写(sliding control of a Matlab procedures, given the M SINULINK documents and the simulation, S-function module prepared)