Intel_Architecture_Software_Developer_Manual

this is apiby8D8psk captured signal for those who wants to check their algorithm for modulation classification and symbol rate estimation symbol rate used 1Mbps fs=20 or 40 MSPs and fc=5 MSPS

说明：  矩阵填充matrix completion的3种方法IHT,IST,NONCVX代码和demo(The matrix filled matrix completion methods IHT, IST, NONCVX code and demo)

matlab图形位置转换，图像识别位移等功能的实现(matlab graphical position conversion, image recognition and displacement functions to achieve)

已知采样频率80000，通带衰减0.5阻带衰减45 通带截止频率4000，阻带截止频率20000，用双线性变换法设计数字低通滤波器 (Known sampling frequency 80000, attenuation in the passband stop-band attenuation 45 0.5 Passband cutoff frequency of 4000, 20,000 stopband cutoff frequency, using bilinear transform design digital low-pass filter)

蚁群算法的MATLAB程序，提供变量初始化 C=[1304 2312 3639 1315 4177 2244 3712 1399 3488 1535 3326 1556 3238 1229 4196 1004 4312 790 4386 570 3007 1970 2562 1756 2788 1491 2381 1676 1332 695 3715 1678 3918 2179 4061 2370 3780 2212 3676 2578 4029 2838 4263 2931 3429 1908 3507 2367 3394 2643 3439 3201 2935 3240 3140 3550 2545 2357 2778 2826 2370 2975] m=31 Alpha=1 Beta=5 Rho=0.9 Q=100 NC_max=200 (Ant colony algorithm of MATLAB procedures, initialize the variable C = [1304 2312 3639 1315 4177 2244 3712 1399 3488 1535 3326 1556 3238 1229 4196 1004 4312 790 4386 570 3007 1970 2562 1756 2788 1491 2381 1676 1332 695 3715 1678 3918 2179 4061 2370 3780 2212 3676 2578 4029 2838 4263 2931 3429 1908 3507 2367 3394 2643 3439 3201 2935 3240 3140 3550 2545 2357 2778 2826 2370 2975] m = 31 Alpha = 1 Beta = 5 Rho = 0.9 Q = 100 NC_max = 200 )

Transmission for a multilayer structure versus frequency(GHz)

遗传算法优化多峰函数，最优值约在38.8左右，亲测可用(Multimodal function optimization genetic algorithm, the optimal value of about 38.8 or so, pro-test available)

This ia s simple Matlab code on image processing. It perform a negative on image, enhance the image and convert the image to gray-scale.

MATLAB的M语言编写，用于解决机器追踪的问题。机器状态估计由minimax滤波器完成。(This m-file simulates a vehicle tracking problem.The vehicle state is estimated with a minimax filter.In addition,with the a priori knowledge that the vehicle is on a particular road, the vehicle state is estimated with a constrained minimax filter. )

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.)