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SVM for Classification and Regression,其文中附有相应的网址，并可以下载SVM，结合相应的实例进行讲解(SVM for the Classification and Regression. his article with the corresponding web site and can be downloaded SVM, with the corresponding example to explain)

Euler方法求解微分方程的源程序，很实用，绝对正确，还有画图功能，图形中描出点来，简单易懂。(Euler method for solving differential equations of the source, very practical, absolutely right, there are drawing function, points to delineate the graphic, easy to understand.)

上传内容为matlab的神经网络函数工具箱，包含各种实现例程。(Upload content to the neural network function matlab toolbox contains a variety of routine implementation.)

说明：  基于瞬时线形混合模型的语音信号分离的MATLAB程序(Instantaneous linear mixing model based on speech signal separation MATLAB program)

自己利用MATLAB中的S-FUNCTION搭建的空间矢量脉宽调制SVPWM系统。(Their use in MATLAB S-FUNCTION to build the space vector pulse width modulation SVPWM system.)

基于bp网络的最大误差逆向传播算法的实现(Maximum error back- propagation algorithm implementation based on BP network)

扇形传感器区域覆盖优化的虚拟力导向粒子群算法(Fan-shaped area coverage sensor-driven power optimization of the virtual particle swarm optimization)

说明：  块状导频的OFDM信道估计ofdmchannelest4为2008年本科毕业设计(Pilot block of the OFDM channel estimation ofdmchannelest4 for the 2008 design graduate)

a very nice book of SCFDMA (Single carrier frequency division multiplexing). Also contains the simulation of the scfdma system in matlab.

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.