登录
首页 » matlab » GNN_1_1b

GNN_1_1b

于 2020-07-03 发布 文件大小:473KB
0 223
下载积分: 1 下载次数: 18

代码说明:

  基于GNN神经网络的系统仿真,具有较好的仿真效果。(Based on GNN neural network system simulation, has a good simulation results.)

文件列表:

GNN_1_1b
........\GNN 1.1b
........\........\comparisonNet
........\........\.............\initializeComparisonNet.m,1962,2007-12-15
........\........\.............\learnComparisonNet.m,5195,2007-12-15
........\........\.............\plotComparisonNetTrainingResults.m,613,2007-12-15
........\........\.............\testComparisonNet.m,7469,2007-12-15
........\........\Configure.m,39956,2011-03-01
........\........\datasets
........\........\........\CliqueDataset.config,1039,2007-12-15
........\........\........\HalfHotDataset.config,892,2007-12-15
........\........\........\makeCliqueDataset.m,9487,2007-12-15
........\........\........\makeCliqueDataset_fix_rand.m,9786,2007-12-15
........\........\........\makeGeneralDataset.m,8650,2007-12-15
........\........\........\makeHalfHotDataset.m,11774,2007-12-15
........\........\........\makeMutagenicDataset.m,13115,2013-02-11
........\........\........\makeNeighborsDataset.m,9303,2007-12-15
........\........\........\makeOddEvenDataset.m,7952,2007-12-15
........\........\........\makeParityDataset.m,7941,2007-12-15
........\........\........\makeSecondOrderNeighborsDataset.m,9856,2007-12-15
........\........\........\makeSubGraphDataset.m,11308,2007-12-15
........\........\........\makeTmpDataset.m,1891,2007-12-15
........\........\........\makeTreeDepthDataset.m,9592,2007-12-15
........\........\........\makeWebPagesScoringDataset.m,10743,2007-12-15
........\........\........\muta-f.pl,390315,2007-12-15
........\........\........\muta-u.pl,77086,2007-12-15
........\........\........\muta.pl,467401,2007-12-15
........\........\........\muta.pl_new,357429,2007-12-15
........\........\........\NeighborsDataset.config,854,2007-12-15
........\........\........\ParityDataset.config,806,2007-12-15
........\........\........\SecondOrderNeighborsDataset.config,875,2007-12-15
........\........\........\SubGraphMatchingDataset.config,1120,2007-12-15
........\........\........\TreeDepthDataset.config,788,2007-12-15
........\........\........\TreeDepthDataset.config.backup,808,2007-12-15
........\........\........\WebPagesScoringDataset.config,868,2007-12-15
........\........\experiments
........\........\...........\init_class.m,432,2007-12-15
........\........\...........\save_learning.m,1046,2007-12-15
........\........\...........\start_learning.m,161,2007-12-15
........\........\...........\test_learning.m,1600,2007-12-15
........\........\GNN.config,2857,2011-03-01
........\........\GNN_DOC.pdf,190123,2011-07-21
........\........\initialization
........\........\..............\initializeNet.m,1547,2007-12-15
........\........\isomorphism
........\........\...........\areIsomorph.m,1664,2007-12-15
........\........\...........\isomorphism.mat,4295,2007-12-15
........\........\...........\mygetPR.m,282,2007-12-15
........\........\...........\mytest.m,287,2007-12-15
........\........\learn.m,552,2007-12-15
........\........\MLP
........\........\...\initializeMLP.m,1653,2007-12-15
........\........\...\testMLP.m,2656,2007-12-15
........\........\...\trainMLP.m,4954,2007-12-15
........\........\neuralNetworks
........\........\..............\backwardOneLayerLinearOutNet.m,431,2007-12-15
........\........\..............\backwardOneLayerNet.m,826,2007-12-15
........\........\..............\backwardTwoLayerLinearOutNet.m,725,2007-12-15
........\........\..............\backwardTwoLayerNet.m,982,2007-12-15
........\........\..............\forwardJacobianOneLayerLinearOutNet.m,166,2007-12-15
........\........\..............\forwardJacobianOneLayerNet.m,239,2007-12-15
........\........\..............\forwardOneLayerLinearOutNet.m,698,2007-12-15
........\........\..............\forwardOneLayerNet.m,340,2007-12-15
........\........\..............\forwardTwoLayerLinearOutNet.m,1207,2007-12-15
........\........\..............\forwardTwoLayerNet.m,1216,2007-12-15
........\........\..............\getDeltaJacobianOneLayerLinearOutNet.m,368,2007-12-15
........\........\..............\getDeltaJacobianOneLayerNet.m,521,2007-12-15
........\........\..............\getDeltaJacobianTwoLayerLinearOutNet.m,831,2007-12-15
........\........\..............\getDeltaJacobianTwoLayerNet.m,929,2007-12-15
........\........\..............\getJacobianOneLayerLinearOutNet.m,781,2007-12-15
........\........\..............\getJacobianTwoLayerLinearOutNet.m,780,2007-12-15
........\........\private
........\........\.......\displayTestRes.m,2271,2007-12-15
........\........\.......\evaluateAccuracyOnGraphs.m,652,2007-12-15
........\........\.......\learn_.m,20232,2007-12-15
........\........\.......\test4autoassociator.m,14720,2007-12-15
........\........\.......\test4autoassociator_old.m,17292,2007-12-15
........\........\.......\test4autoassociator_veryold.m,11827,2007-12-15
........\........\.......\test4classification.m,12806,2011-03-11
........\........\.......\test4regression.m,9993,2011-03-11
........\........\.......\test4uniform.m,5827,2007-12-15
........\........\save_experiment.m,376,2007-12-15
........\........\startSession.m,72,2011-03-01
........\........\systemModels
........\........\............\autoassociatorComputeDeltaError.m,637,2007-12-15
........\........\............\autoassociatorComputeError.m,1456,2007-12-15
........\........\............\linearModelInitialize.m,1128,2007-12-15
........\........\............\linearModelRunBackward.m,3807,2007-12-15
........\........\............\linearModelRunForward.m,2208,2007-12-15
........\........\............\mseComputeDeltaError.m,654,2007-12-15
........\........\............\mseComputeError.m,1344,2007-12-15
........\........\............\neuralModelAutomorphComputeError.m,1651,2007-12-15
........\........\............\neuralModelGetDeltaJacobian.m,1265,2007-12-15
........\........\............\neuralModelGetJacobian.m,1837,2007-12-15
........\........\............\neuralModelInitialize.m,6488,2007-12-15
........\........\............\neuralModelQuadraticComputeDeltaError.m,587,2007-12-15
........\........\............\neuralModelQuadraticComputeError.m,1063,2007-12-15
........\........\............\neuralModelRunBackward.m,1285,2007-12-15
........\........\............\neuralModelRunForward.m,1555,2007-12-15
........\........\............\neuralModelWithProductComputeDeltaError.m,1308,2007-12-15

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • 2345网
    用于天气爬虫,主要是从2345天气网进行获取历史天气(Used for weather reptiles, mainly from the 2345 Weather Network for historical weather)
    2017-09-30 16:32:27下载
    积分:1
  • surf特征识别与多图像特征匹配与误匹配矫正
    说明:  本程序基于matlab,诠释了surf特征的提取、匹配过程及误匹配的矫正(this program is for surf feature processing)
    2020-01-05 18:33:00下载
    积分:1
  • ECE
    ultimate papers usefully all time projects for engineering students..
    2013-03-02 18:28:59下载
    积分:1
  • 人工势场法(3维alpha)
    人工势场三维仿真图,程序可以运行。。。。。。。。(Artificial potential field three-dimensional simulation diagram , the program can run.)
    2021-02-21 22:49:41下载
    积分:1
  • C#数据保存至csv文件
    C#保存数据至*.csv进行显示,新建.csv文件并完成读写操作。(C# saves data to *.csv to display.)
    2017-12-11 21:30:28下载
    积分:1
  • Snake
    采用swing实现贪吃蛇游戏的开发,食物的自动生成以及蛇的运动。(Snake game using swing to achieve the development of the automatic generation and the snake food movement.)
    2011-11-25 15:58:27下载
    积分:1
  • vc的一些原码,对于帮助学习和提高很有帮助
    vc的一些原码,对于帮助学习和提高很有帮助-vc some of the original code, for help to learn and improve very helpful
    2022-05-24 03:52:08下载
    积分:1
  • 软件工程课件,介绍软件开发的技术,方法,原理(16
    软件工程课件,介绍软件开发的技术,方法,原理(16-20)章-Software engineering courseware, introduction of software development techniques, methods, principles (16-20) Chapter
    2023-04-15 13:15:04下载
    积分:1
  • lunwenlishuju
    不同机动方式下的双机无源定位效果比较,应用了KAMLAN滤波,对研究纯方位定位有帮助!(Under different mobility of two-plane effects of passive positioning, the application of the KAMLAN filtering, the study of bearing-only location has helped!)
    2021-04-01 18:29:08下载
    积分:1
  • am2120
    am2120驱动代码,在keil环境当中可以直接使用;并且其中包含获取温湿度数据的接口函数(AM2120 driver code can be used directly in keil environment. And it contains the interface function to get the temperature and humidity data)
    2018-09-11 09:36:00下载
    积分:1
  • 696518资源总数
  • 106155会员总数
  • 8今日下载