DynSimulat

一篇非常优秀的论文：合成孔径雷达成像matlab仿真，附PDF和源码。 (Synthetic Aperture Radar Imaging Simulated in MATLAB（PDF and Matlab code）)

说明：  Object-oriented programming

用了一个多小时才传俩 光学相差程序 MATLAB编写 欢迎指教(MATLAB and discrib the abrration )

matlab中用不同的方法计算随机数列的功率普(matlab using different methods of calculating the random numbers out of power )

将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序(Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality reduction. To recover a signal from its compressive measurements, standard CS algorithms seek the sparsest signal in some discrete basis or frame that agrees with the measurements. A great many applications feature smooth or modulated signals that are frequency sparse and can be modeled as a superposition of a small number of sinusoids. Unfortunately, such signals are only sparse in the discrete Fourier transform (DFT) domain when the sinusoid frequencies live precisely at the center of the DFT bins. When this is not the case, CS recovery performance degrades significantly. In this paper, we introduce a suite of spectral CS (SCS) recovery algorithms for arbitrary frequency sparse signals. The key ingredients are an over-sampled DFT frame, a signal model that inhibits closely spaced sinusoids, and classical sinusoid parameter e)

包括数字图像直方图绘制，数字图像直方图匹配，数字图像基于阈值分割算法(Including digital image histogram drawing, digital image histogram matching, digital image segmentation algorithm based on the threshold)

可利用feko得到回波或根据公式构造回波，基于字典缩放的属性散射中心的参数提取，并重构回波(The echo can be obtained by using FEKO, or the echo can be constructed according to the formula. The parameters of the scattering center of the dictionary are extracted based on the dictionary scaling and the echo is reconstructed.)

adboost分类器 matlab源程序 用于训练样本 实现分类 (adboost classfication)

far field modelling of active optical fibre 2 core

BP神经网络详解与实例，包括多种操作实例与演示说明(BP neural network Xiangjie instructions and examples, including a variety of operating instance with demo)