埃及加拿大--编队成形--针对成形的稳定性问题

algorithm can be easily implemented in matlab

是关于MATALB 神经网络与VB的混合编程,希望对大家有所帮助(On neural network MATALB mixed with VB programming, and they hope to help everyone)

说明：  该程序介绍Matlab时频分析技术及其应用，利用该程序可以分析周期信息(This program is used to get the frequence. )

清理c程序注释的matlab小程序，仅供学习交流!(Matlab program to clean up the c programming notes for learning exchanges....)

Buck变换器是最常用的变换器，工程上常用的拓扑如正激、半桥、全桥、推挽等也属于Buck族，其中Buck变换器补偿网络设计，是开关电源的重要研究课题，本文将针对基于PI控制方式的4A开关电源进行设计和Multisim的仿真研究。(Buck converter is the most commonly used converter on the topology of the project, such as forward, half bridge, full bridge, push-pull, the Buck family, Buck Converter compensation network design is an important research topic of the switching power supply, this paper4A-based PI control switching power supply design and Multisim simulation study)

说明：  Matlab image inpainting using deep learning

这是MATLAB小型的。下下去看看嘛，活血对你以后的学习有帮助(This is a small MATLAB. To see them go under, Huoxue after learning of your help)

BP（Back Propagation）网络是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。 BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。 它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hide layer)和输出层(output layer)。 通过对信息的提取以及记忆，用作分类、聚类、预测等。 (BP (Back Propagation) network is a pre-press error back propagation algorithm Multilayer feedforward network, is one of the most widely used neural network model. BP network can learn and store a large amount of input- output mode mapping without prior reveal mathematical equations that describe the mapping relationship. It s learning rule is to use the steepest descent method, by reverse spread to constantly adjust the network weights and thresholds and the minimum sum of squared error of the network. BP neural network topology comprises an input layer (input), hidden layer (hide layer) and an output layer (output layer). By extracting information and memory, it is used as classification, clustering, prediction.)

Content based image retrieval using color histogram and shape

Particle Swarms Optimization