adodb

瑞利衰落仿真编写和瑞利衰落包络的编程，内有详细说明(The preparation of Rayleigh fading simulation programming Rayleigh fading envelope)

振动信号时域处理办法，包括低通、带通滤波和频域积分法(Time-domain vibration signal processing options, including low-pass, band-pass filtering and frequency-domain integral method)

考虑L的三个不同值：L＝256（3个数据段），L＝128(7个数据段)和L=64（15个数据段）。各自的谱估计图如上图所示。可以明显的看到，加窗明显的减小了频谱上的假谱峰，但也更加进一步平滑了谱峰。所以，对于L＝64的情况，在ω＝0.8π的谱线可以很确定的辨认，但是那两个靠近的谱峰不容易区分。对于L＝128的情况，这种情况提供了在分离和检测间最好的均衡。当然，对于在L＝256时的情况，效果是更好的，能够从谱估计图上明显的分辨出三条谱线的存在以及它们幅度关系的强弱。 除了Welch法外，还可以采用对多个周期图求平均的功率谱估计方法的其他方法如Bartlett法等等，在功率谱估计上也能取得较好的结果。(consider three different values : L = 256 (3 data), L = 128 (7 data) and L = 64 (15 data). Their spectral estimation map as shown in Fig. It is clear to see that increase significantly decreasing window of the spectrum of false peaks, but much more to further smooth the peaks. Therefore, L = 64, in the case = 0.8 spectrum can determine the identification, but that the two peaks around is not easy to distinguish. L = 128 for the situation, which provided the separation and detection among the best balanced. Of course, L = 256 in the case, the effect is better, from the spectral estimation map clearly distinguish between the three lines of the existence and their relationship to the rate of strength. In addition to Welch law, but also can be used to map multiple cycle for the average power)

采用时域平滑FAM法画出的信号循环谱图，其中包括FAM子函数和画图的主函数(FAM time-domain method used to draw a smooth spectrum of the signal cycle, including FAM Functions and main function of drawing)

viterbi算法的matlab实现，主要用于数字通信中接收端的译码(viterbi)

压缩传感，压缩感知，压缩采样，稀疏表达，稀疏表示，的入门例子-compressive sensing compressed sensing(compressive sensing compressed sensing)

圆阵多维波达方位估计算法，可以解左右模糊的方位估计算法(The estimation algorithm circular array Duoweiboda position solution fuzzy around the azimuth estimation algorithm)

为实现合成孔径雷达（SAR）图像分类算法的测试与评估，将VC/Matlab 混合编程技术应用到SAR 图像分类平台开发中，分析与 比较了4 种VC/Matlab 混合编程方法及各自优缺点，并着重研究了基于组件对象模型（COM）的VC/Matlab 混合编程方法。使用Matlab COM 编译器创建了SAR 图像分类算法组件，在VC 中调用其导出的接口函数。在此基础上，完成了SAR 图像分类平台的实例开发且 可脱离Matlab 环境运行。实验结果表明，该方法较好地发挥了VC 与Matlab 各自的优势，提高了SAR 图像分类平台开发的效率。(In order to test synthetic aperture radar （SAR） image classification algorithm，VC/Matlab mixed programming technology was used in SAR image classification platform development. Four VC/Matlab mixed programming methods were introduced and analyzed. Comparing with other three methods，the method based on component object model （COM） was studied particularly. SAR image classification algorithm component was created by Matlab COM complier，and its interface function could be invocated with VC. Using this method，a SAR image classification platform was realized. The platform could run without Matlab. The experimental result shows a good combination of VC and Matlab. So，developing efficiency could be enhanced a lot.)

matlab编写的有关神经网络的三个小程序，其中包含bp网络，lvq网络和sofm网络(matlab prepared by the neural network of three small program, which includes bp network, lvq networks and sofm Network)

this is a .mdl file and i have used matlab9