distance

此matlab程序可用来计算mie散射各项参数，计算时需首先输入几个参数，大家可看看程序，然后就懂了(The matlab calculation mie scattering is used to the parameters)

Digital Signal Processing Charles Darwin University Lab7

Neural Predictive Control using Quasi Newton Optimization

simple samples matlab(matlab easy introduction)

对模拟信号抽样，然后进行离散傅里叶变换，利用自编DFT函数，得到频谱，然后进行频谱的还原。(Sampling the analog signal, then the discrete Fourier transform, DFT self function obtained spectrum and the spectrum reduction.)

合成孔径雷达（SAR)目标成像仿真，用平面波展开法计算二维声子晶体带隙,包括最后计算压缩图像的峰值信噪比和压缩效果的源码。( Synthetic Aperture Radar (SAR) imaging simulation target, Computation Method D phononic bandgap plane wave, Including the final calculation of the compressed image peak signal to noise ratio and compression of the source.)

说明：  深度神经网络在函数近似中表现优越，然而需要从头开始训练。另一方面，贝叶斯方法，像高斯过程（GPs），可以利用利用先验知识在测试阶段进行快速推理。然而，高斯过程的计算量很大，也很难设计出合适的先验。本篇论文中我们提出了一种神经模型，条件神经过程（CNPs），可以结合这两者的优点。CNPs受灵活的随机过程的启发，比如GPs，但是结构是神经网络，并且通过梯度下降训练。CNPs通过很少的数据训练后就可以进行准确的预测，然后扩展到复杂函数和大数据集。我们证明了这个方法在一些典型的机器学习任务上面的的表现和功能，比如回归，分类和图像补全(Deep neural networks perform well in function approximation, but they need to be trained from scratch. On the other hand, Bayesian methods, such as Gauss Process (GPs), can make use of prior knowledge to conduct rapid reasoning in the testing stage. However, the calculation of Gauss process is very heavy, and it is difficult to design a suitable priori. In this paper, we propose a neural model, conditional neural processes (CNPs), which can combine the advantages of both. CNPs are inspired by flexible stochastic processes, such as GPs, but are structured as neural networks and trained by gradient descent. CNPs can predict accurately with very little data training, and then extend to complex functions and large data sets. We demonstrate the performance and functions of this method on some typical machine learning tasks, such as regression, classification and image completion.)

《MATLAB7.0从入门到精通》全书源码，包括使用说明。(MATLAB7.0 From Novice to Professional book source code, including instructions for use.)

复杂网络小世界模型，模拟小世界模型 复杂网络小世界模型，模拟小世界模型(he parameter of the small-world model The total number of the network The mean degree is 2*m The remove probability The connection matrix The initial regular network)

MatLab图形绘制功能口令及代码，很不错，值得看看(MatLab graphics rendering capabilities password and code, very good, worth a look)