FreeRTOS源码详解与应用开发 基于STM32

通过sqlserver及VS做的一款管理系统，并附有相应论文

目 录第一章 旅游管理系统概述 11.1社会背景 11.2技术背景 21.2.1数据库概述 21.2.2 Visual Basic概述 31.3 系统开发任务概述 3第二章 旅游管理系统可行性研究及需求分析 42.1项目概述 42.1.1 系统目标 42.1.2 用户特点 42.1.3 运行环境 42.2可行性研究 42.3数据流图 52.4数据字典 7第三章 旅游管理系统总体设计 93.1 数据库设计 93.1.1 数据库设计概述 93.1.2 数据库概念结构设计 93.1.3 数据库逻辑结构设计 103.1.4 数据库的物理结构设计 113.1.5

这是一个用matlab编写的有限差分的声波方程正演的程序。希望对大家有用~

关于移动机器人路径规划的ppt，参考了大量文献，涵盖了几乎可以看到的所有成熟路径规划算法并且加入了很多作者本人的理解。希望对需要的朋友有所帮助。-on mobile robot path planning ppt reference to the vast body of literature, cover almost all can see the maturity path planning algorithm and to the many authors I understand. Hope to a friend in need of help.

基于MAYTLAB实现的利用FFT实现快速卷积，数字信号处理试验。

Xilinx_Zynq-7000 封装库 Altium Designer

稀疏自编码深度学习的Matlab实现，sparse Auto coding，Matlab codetrain, m/7% CS294A/CS294W Programming Assignment Starter CodeInstructions%%%This file contains code that helps you get started ontheprogramming assignment. You will need to complete thecode in sampleIMAgEsml sparseAutoencoder Cost m and computeNumericalGradientml For the purpose of completing the assignment, you domot need tochange the code in this filecurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencodtrain.m∥%%========%6% STEP 0: Here we provide the relevant parameters valuesthat willl allow your sparse autoencoder to get good filters; youdo not need to9 change the parameters belowvisibleSize =8*8; number of input unitshiddensize 25number of hidden unitssparsity Param =0.01; desired average activation ofthe hidden units7 (This was denoted by the greek alpharho, which looks like a lower-case pcurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod4/57train.,m∥in the lecture notes)1 ambda=0.0001%o weight decay parameterbeta 3%o weight of sparsity penalty term%%==:79 STEP 1: Implement sampleIMAGESAfter implementing sampleIMAGES, the display_networkcommand shouldfo display a random sample of 200 patches from the datasetpatches sampleIMAgES;display_network(patches(:, randi(size(patches, 2), 204, 1)), 8)%为产生一个204维的列向量,每一维的值为0~10000curer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod5/57train.m/v%中的随机数,说明是随机取204个 patch来显示%o Obtain random parameters thetatheta= initializeParameters ( hiddenSize, visibleSize)%%=============三三三三====================================97 STEP 2: Implement sparseAutoencoder CostYou can implement all of the components (squared errorcost, weight decay termsparsity penalty) in the cost function at once, butit may be easier to do%o it step-by-step and run gradient checking (see STEP3 after each stepWecurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod6/57train. m vb suggest implementing the sparseAutoencoder Cost functionusing the following steps(a) Implement forward propagation in your neural networland implement the%squared error term of the cost function. Implementbackpropagation tocompute the derivatives. Then (using lambda=beta=(run gradient Checking%to verify that the calculations corresponding tothe squared error costterm are correctcurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod7/57train. m vl(b) Add in the weight decay term (in both the cost funcand the derivativecalculations), then re-run Gradient Checking toverify correctnessl (c) Add in the sparsity penalty term, then re-run gradiChecking toverify correctnessFeel free to change the training settings when debuggingyour%o code. (For example, reducing the training set sizecurer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod8/57train m vl/number of hidden units may make your code run fasterand setting betaand/or lambda to zero may be helpful for debuggingHowever, in yourfinal submission of the visualized weights, please useparameters web gave in Step 0 abovecoS七grad]sparseAutoencoderCost(theta, visibleSize,hiddensize, lambda,sparsityParam, beta,patches)二〓二二二二二二二〓二〓二〓二〓=二====〓=curer:YiBinYUyuyibintony@163.com,WuYiUniversityning, MATLAB Code for Sparse Autoencod9/57train.m vlll96% STeP 3: Gradient CheckingHint: If you are debugging your code, performing gradienchecking on smaller modelsand smaller training sets (e. g, using only 10 trainingexamples and 1-2 hiddenunits) may speed things upl First, lets make sure your numerical gradient computationis correct for a%o simple function. After you have implemented computeNumerun the followingcheckNumericalGradientocurer:YiBinYUyuyibintony@163.com,WuYiUniversityDeep Learning, MATLAB Code for Sparse Autoencode10/57

学会不同搜索法（最速下降法，共轭梯度法，牛顿法，拟牛顿法）的计算步骤； 比较不同搜索法（最速下降法，共轭梯度法，牛顿法，拟牛顿法）的优缺点

【实例简介】220交流电转直流电的电路图，含有详尽的设计说明，朋友们多支持啊~~

通过Matlab模拟了随机产生的一定概率分布的信号序列,叠加高斯噪声后利用最大后验概率(MAP)检测到的误码率,做出BER～SNR曲线,并与理论计算得到的曲线进行比较,两者吻合