ASR

基于信道的历史信息来预测不同信道的未来可用时间可以帮助CR选择一个最佳信道进行信息传递。不同的预测准则应用到周期或是随机的开关模式中。一个CR可以学习以往不同信道的模式。我们提出一个简单的分类和学习方法去检测模式的类型和收集需要的信息用于智能信道的选择。MATLAB仿真结果显示提出的方案在随机信道的随机和周期模式中都有优越的表现。随着时间的变化，新到的切换次数减少到55 ，并且延迟时间也相应减少，而吞吐量却在提高。(Prediction of future availability times of different channels based on history information helps a cognitive radio (CR) to select the best channels for control and data transmission. Different prediction rules apply to periodic and stochastic ON-OFF patterns. A CR can learn the patterns in different channels over time. We propose a simple classification and learning method to detect the pattern type and to gather the needed information for intelligent channel selection. Matlab simulations show that the proposed method outperforms opportunistic random channel selection both with stochastic and periodic channel patterns. The amount of channel switches needed over time reduces up to 55 , which reduces also the delay and increases the throughput.)

说明：  这是一个图论工具箱，内包含25个图论算法，包括最小路径规划，和旅行商问题。(This is a map of the toolbox, which contains 25 plans of algorithms, including the smallest path planning, and the traveling salesman problem.)

principal component analysis

PSO算法的实现。寻找搜寻范围内的最优解。(PSO algorithm. Search within to find the optimal solution.)

matlab neural network and wavelet price prediction

Spectrum Sensing in Cognitive Radio Approach in Matlab

在OFDM系统 中，宽带信道被分割相互重叠的窄带子信道，如果各子信道 的带宽比信道的相干带宽要小，那么信号传输就有可能在无 频率选择性衰落或者平坦衰落的信道进行。(In OFDM system The wideband channel is divided into narrowband sub-overlapping, if each sub- The bandwidth is less than the coherence bandwidth of the channel, the signal transmission is possible without Frequency selective fading or flat fading channels.)

基于rls算法的多麦克风降噪matlab程序代码(Matlab code based on the the rls algorithm of multi-microphone noise reduction)

这是一个展示Binding功能的例子，实现了滑动条控制矩形坐标的功能。(This is a showcase Binding features examples slider control to achieve a rectangular coordinate functions.)

图像超分辨率重建算法，通过稀疏混合估计来实现，效果不错。(Image super-resolution reconstruction algorithm, by mixing estimates sparse achieved good results.)