work

平面框架结构MATLAB源程序，可以计算任意平面框架结构。(MATLAB source of Plane frame structure that you can calculate any plane frame structure.)

chapter 6 with examples and figures

from wikipedia: Integration is an important concept in mathematics and, together with its inverse, differentiation, is one of the two main operations in calculus. Given a function f of a real variable x and an interval [a, b] of the real line, the definite integral

加入重复控制，是机器学习的例程，用于信号特征提取、信号消噪。( Join repetitive control, Machine learning routines, For feature extraction, signal de-noising.)

matlab包括最基本的语音处理程序（如谱减法，谱幅度估计，语谱图等）以及语音库(Located in this Prentice Hall web site compartment are functions, scripts, workspaces, and data required by the MATLAB exercises in the text: Discrete-Time Speech Signal Processing: Principles and Practice. Note that the speech files given are often specific cases of a certain class of speech signal, i.e., the waveforms often can be replaced by other examples with similar characteristics that serve the instructive purpose of the exercise.)

To emmbed a Matlab code (m file) in your delphi application and send numerical values to Matlab for calculation, This file can Help.

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.)

matlab信号处理详解，希望可以对大家有用！！！！！！(matlab signal processing Xiang Jie, I hope we can be useful! ! ! ! ! !)

Marr Hildreth Edge Detector

A hill climbing algorithm for finding the minimum of a function fitnessfun in the real space.