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第1章MATLAB操作基础 第2章MATLAB矩阵及其运算 第3章MATLAB程序设计 第4章MATLAB文件操作(Chapter 1 MATLAB operation based on MATLAB matrix in Chapter 2 and Chapter 3 of computing MATLAB Programming Chapter 4 MATLAB file operations)

implementation of feedforward neural network to recognize the faces with sunglasses from open faces.data source is from machine learning book by mitchell

用JACOBI迭代法求解线性代数方程组，此迭代法是数值计算基本方法之一。(Use JACOBI iterative method for solving linear algebraic equations, and this iteration method is one of the basic method of numerical calculation.)

设计了柔性机器人的反演控制，并进行仿真分析。柔性机械臂的动力学方程具有高度非线性、强耦合以及时变等特点。(nversion control of flexible robot design and simulation analysis. Dynamic equations of flexible manipulator is highly nonlinear, strong coupling and time-varying characteristics.)

matlab在土木工程领域运用，有限元程序，求解振型和频率，给出了阵型图。程序已模块化(matlab use in the field of civil engineering, finite element program, to solve the vibration modes and frequencies are given in Figure formation. Program has a modular)

说明：  多假设跟踪Matlab代码例子,也是从别的地方下载的(example of MHT target tracking)

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.)

image segmentation , rsf with demo and ...

Mathematical Model and Six-Degree-of-Freedom Simulation of a Business Jet Aircraft

And OR Not gate in cellular learning automata