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DL : 0
The doggie found a bone in an ancient maze, which fascinated him a lot. However, when he picked it up, the maze began to shake, and the doggie could feel the ground sinking. He realized that the bone was a trap, and he tried desperately to get out of this maze. The maze was a rectangle with sizes N by M. There was a door in the maze. At the beginning, the door was closed and it would open at the T-th second for a short period of time (less than 1 second). Therefore the doggie had to arrive at the door on exactly the T-th second. In every second, he could move one block to one of the upper, lower, left and right neighboring blocks. Once he entered a block, the ground of this block would start to sink and disappear in the next second. He could not stay at one block for more than one second, nor could he move into a visited block. Can the poor doggie survive? Please help him.(The input consists of multiple test cases. The first line of each test case contains three integers N, M, and T (1 < N, M < 7; 0 < T < 50), which denote the sizes of the maze and the time at which the door will open, respectively. The next N lines give the maze layout, with each line containing M characters. A character is one of the following: 'X': a block of wall, which the doggie cannot enter; 'S': the start point of the doggie; 'D': the Door; or '.': an empty block.)
Update : 2024-05-08 Size : 1024 Publisher : zilewwy

Other4
DL : 0
本MATLAB代码采用的是用M序列伪随机序列作为输入,测试系统的脉冲响应,采用离散算法。(This MATLAB code uses the M sequence pseudorandom sequence as input to test the impulse response of the system, using the matrix algorithm.)
Update : 2024-05-08 Size : 2048 Publisher : 阳光的呵呵卡

DL : 2
基于MATLAB的汽车电动助力转向系统转向特性分析,包含m文件,simulink模型。亲测可用。具有很强的通用性。(The steering characteristic analysis of automotive electric power steering system based on MATLAB includes m file and Simulink model. The test is available. It has a strong generality.)
Update : 2024-05-08 Size : 977920 Publisher : 陈三2

DL : 1
一些分类器尝试,包括SVM,KNN,自带树与adaboost或者bagging结合等。(Some classifiers test,such as SVM,KNN,etc, including test data. Only some of the methods are included in the main.m.)
Update : 2024-05-08 Size : 1804288 Publisher : 隐笑

这是一个变速变桨距控制的9MW风力发电并网系统(DFIG),先运行.m文件,设定Ts=5e-6s。亲测有效(This is a variable speed pitch control 9MW wind power generation grid connected system (DFIG). First, run the.M file and set Ts=5e-6s. Pro test effectiveness)
Update : 2024-05-08 Size : 98304 Publisher : 最帅的胖子

这是哈尔滨工业大学数字信号处理课的课程设计作业,利用窗函数涉及滤波器分别对自己设定的测试信号和老师给定的连续频谱信号进行滤波。 我编写时先后在同一个M文件中写了很多的画图语句,如果直接F5运行,它们会互相覆盖,使用时请将需要的绘图代码复制到命令行中重新运行。(This is the course design assignment of Digital Signal Processing Course of Harbin University of Technology. The window function is used to filter the test signal set by yourself and the continuous spectrum signal given by the teacher.)
Update : 2024-05-08 Size : 3072 Publisher : Wicjpy

DL : 0
在MTLAB环境运行main_msbcsspl.m。该程序的功能是实现图像的稀疏分解并重建图像,采用压缩感知理论,利用小波分析,在小波域分块观测,可以用很少的观测值就能重建原图像。程序包中已经整合了小波包和测试图像,没有多余文件,程序经过亲测并修改,能在MATLAB中直接运行得到很好的结果,速度非常快!(Run main_msbcsspl.m in the MTLAB environment. The function of the program is to decompose and reconstruct the image sparsely. Using compressed sensing theory and wavelet analysis, the original image can be reconstructed with very few observations. Wavelet package and test image have been integrated in the package. There are no redundant files. After testing and modifying the program, it can run directly in MATLAB and get good results. The speed is very fast.)
Update : 2024-05-08 Size : 2601984 Publisher : 胡戈

包含三个M文件,程序为本人自行编译完成,Demo中设有仿真信号验证,并经本人实际齿轮箱信号(轴承外圈故障)测试,经包络分析结果显示能够有效定位轴承外圈故障频率。 亲测可用。(It contains three M files. The program is compiled and completed by myself. Demo has simulation signal validation. It has been tested by my actual gear box signal (bearing outer ring fault). The envelope analysis results show that it can effectively locate the bearing outer ring fault frequency. The pro-test is available.)
Update : 2024-05-08 Size : 3072 Publisher : 曾经的水

MKtest
DL : 0
% Mann-Kendall突变检测 % 数据序列y % 结果序列UFk,UBk2 %-------------------------------------------- %读取excel中的数据,赋给矩阵y %获取y的样本数 %A为时间和径流数据列(M-K trend test of serial data)
Update : 2024-05-08 Size : 79872 Publisher : 流翼之城

这是一款采用Matlab编写的语音识别界面,对情感语音进行模板培训。运行main.m,在界面选择待测试音频文件,运行后即可在界面看到检测结果。(This is a speech recognition interface written in matlab, which trains emotional speech template. Run main.m and select the audio files to be tested in the interface. After running, the test results can be seen in the interface.)
Update : 2024-05-08 Size : 8192 Publisher : meiying6526

该压缩包包括两个文件: 1、main.m 将训练数据输入到决策树中,训练并在自动分好的测试数据上测试,并保存训练好的决策树 ctree.mat文件。 2、classification.m 加载训练好的决策树,使用决策树对新输入的数据进行分类。 该方法主要用于对SLIC超像素块进行分类,稍加修改可以用于其他数据分类。(The compression package consists of two files: 1. Main. m inputs training data into decision tree, trains and tests on automatically graded test data, and saves the trained decision tree ctree. mat file. 2. Classification. m loads the trained decision tree and uses it to classify the new input data. This method is mainly used to classify SLIC super-pixel blocks, and slightly modified can be used for other data classification.)
Update : 2024-05-08 Size : 3072 Publisher : ANR~

试过了好几个成华的660e软件都无法打开最新的测试bin文件,这个是我自己从测试系统提取的,确定可以用(I have tried several Chenghua's 660e software, but I can't open the latest test bin file. This is extracted from the test system by myself. I'm sure it can be used.)
Update : 2024-05-08 Size : 5465088 Publisher : yongaike

植物虫害检测(GUI,注释,svm算法) 该课题为基于MATLAB SVM方法的植物病害检测系统,带GUI界面,可以识别多种被虫害侵蚀的植物叶子,输出结果。带论文和详细注释。 train 对黄瓜子文件夹所有图片提取 颜色矩特征和gabor纹理特征,然后svm训练 test 对测试图像灰度化,滤波,提取 颜色矩特征和gabor纹理特征,然后svm模型测试,输出类别 colorMom.m 颜色矩特征提取 Gabor_palm.m gabor纹理特征提取(Plant pest detection (GUI, annotation, SVM algorithm) The project is a plant disease detection system based on MATLAB SVM method, with GUI interface, which can identify a variety of plant leaves eroded by pests and output results. With paper and detailed notes. Train extracts color moment features and Gabor texture features from all the pictures in the sub folder of cucumber, and then SVM trains them Test grayscale and filter the test image, extract color moment features and Gabor texture features, then SVM model test, output category Colormom. M color moment feature extraction Gabor u Palm. M Gabor texture feature extraction)
Update : 2024-05-08 Size : 6463488 Publisher : for Matlab

folder = 'C:\Users\erinb\Documents\NTNU\Teaching\EWEM_H14\ProjectDescription\xxSRA_models\OC4semi\Decay6'; % folder % where the analysis was carried out bodyNum = 1; % body number motion = 6; %1 for surge, 3 for heave, 5 for pitch, 6 for yaw FFT_tmax = 1000; % maximum time for the FFT plot %(reduce if motions have already died out) endRamp = 360; % start time for decay test matfileName = 'm001.m'; wnForDampCoeff = 2*pi/80.4; % natural frequency in rad/s for damping coefficient % calculation. The damping coefficient calculation will not run for % wnForDampCoeff=0. This should be updated.
Update : 2024-05-08 Size : 414720 Publisher : tariq

No Sleep EA It can work on any demo or live account for unlimited period of time. It also can be back-tested, even I'm not back test believer. Forward test is the best of course. I made 20% in 15 days with only 6.5% DD on EURUSD ... Can work on any pair. Lately, I use it on Gold because of the high lot rebate I got from broker and it's profit as well. So, easily can made 40% a month. You can even make more than 100% but you need to withdraw profit frequently. You can use it on any time frame ... If you want to use multiple pairs, then use safer settings ... If you want to use 1 pair, I recommend GBPUSD or Gold but current settings will not work on gold, you need to use yours to let it go. Lower time frame means higher profit, higher DD ... Higher time frame means lower profit, lower DD ...
Update : 2024-05-08 Size : 28672 Publisher : florent522
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