158 results

A toolbox for Matlab, for solving continuous time trajectory optimization problems

Fast approximate string to double parsing for real or complex numbers.

error checking, user stopping, validating user inputs

This code is explained in the following YouTube Video:While Loops - Validate User Input: https://youtu.be/LyKb1MvCiG8 In this video I cover how to code while loops in MATLAB and how these can be used

Matsim

version 1.0.4

by Marco Gavelli

Matlab/Simulink interface. Easily create Simulink models from a Matlab script.

This demo shows how to implement convolutional neural network (CNN) for image classification with multi-input. カスタムループを用いて複数入力のCNNを実装します。

Image Classification using Convolutional Neural Network with Multi-Input[English]This demo shows how to implement convolutional neural network (CNN) for image classification with multi-input using

validateInput

version 1.0.0.0

by Jed F.

A simple 'getOpts' type script to validate input parameters.

validateInput started when creating saveppt2. There was a need to take a large number of inputs, in any order, and make them usable to the script. Checking if an input argument has been passed can be

Parse varargin cells to option structures

validator functions. This is a utility function based on Matlab's `inputParser`.

HTMLtable

version 1.0.3

by Eric Dziekonski

Generate the code for a CSS/HTML-based data table from an input numeric, string, or cell array with many available formatting options.

element). With 60 user adjustable parameters, and multiple accepted input formats, the table can be customized in virtually any way.All parameters are invoked via name-value pairs and validated.Please read

Like the built-in input function but with the ability to impose constraints and checks on user input

validateattributes(A,classes,attributes).k = VALIDATEDINPUT(prompt,validationFcn) checks the input using the provided validationFcn.If the user input provided at the prompt is invalid, the user will be informed of the reason why and

Matlab-mdtsToolbox

version 1.0.0

by Roland

A Matlab Toolbox to handle mutli-dimensional time series (mdts)

This code aims to perform a prediction of time sequence variable based on three external inputs.

response at time t what will be the response at the time t+1?Outputnet: An accurate open-loop shallow network able to predict the response given three external inputs. Use this network for validation or

PEMF cross-validation

version 2016.1.0.0

by ADAMS Lab

PEMF is predictive (cross-validation type) approach to test surrogate models.

Regression (SVR), and Neural Networks. It can be perceived as a novel sequential and predictive implementation of K-fold cross-validation. PEMF takes as input a model trainer (e.g., RBF-multiquadric or

This demo shows how to classify crack images using deep learning and explain why behind the decision. このデモでは、深層学習によりひび割れ画像を分類し、さらにその特徴量の可視化を

augmentedImageDatastore(inputSize(1:2),imdsTrain, ... 'DataAugmentation',imageAugmenter);To automatically resize the validation and test images without performing further data augmentation, use an augmented image datastore without specifying

simple example of video classification with LSTM

); WData{i}=W(:,StartingFrameNumWalk:StartingFrameNumWalk+ClipDuration);endPrepare Training DataPrepare the data for training by partitioning the data into training and validation partitions.Create Training and Validation PartitionsPartition the data. Assign 70% of the data to the

This algorithm is an extension of the change point analysis to detect general changes in the pattern of a time series.

: https://www.frontiersin.org/articles/10.3389/fpsyg.2020.01970/full. **************************************************************************Updates Version 1.1- outliers are removed from the input time series - function "findchangepts" is used instead of

MATLAB toolbox for stochastically rounded elementary arithmetic operations in IEEE 754 floating-point arithmetic.

It can generate a fundamental sine wave from a distorted input voltage

Follow the instruction as described in the file to validate the best

业务范围包括但不限于,数据分析、信号处理、时频分析、小波变换、微弱特征增强、生物/地震/机械/振动/声音/语音等多种领域中的信号处理问题。(最新文章源码以及c或者python版本,目前优先供给有项目合作的团队)邮箱联系:yugang2010@163.com

, it is perfectly invertible. The MSST does not require any a priori information on the signal. The code only needs the input parameters, e.g., signal, window length and iteration number. It is a

dispstr

version 1.1.1

by Andrew Janke

A Matlab API for extensible, polymorphic custom object display

MATLAB code for abnormal detection using Support Vector Data Description (SVDD)

modelsvdd.train(trainData, trainLabel);% test SVDD modelresults = svdd.test(testData, testLabel);BinaryDataset is designed to validate the svdd model only, you can use your data and please be careful to keep the naming of

Reference code for the paper: Deep White-Balance Editing, CVPR 2020 (Oral).

, Mahmoud and Brown, Michael S}, booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}, year={2020}}Training dataDownload the Rendered WB dataset.Copy both input images

Sensor-Independent Illumination Estimation for DNN Models (BMVC 2019)

compatability error, then try out with Matlab_ver = 'Matlab 2019b'.You can change the model_name and image_name variables to choose between our trained models and to change input image filename, respectively. You

Kannada alphabets datasets are trained to the neural network using MFCC and LPC coefficients and accuracy is compared using confusion matrix

training data set. Common practice is to divide a dataset into training dataset and validation dataset in ration of 4:1. This partition helps the network to predict the accuracy of trained network.Choose

This demo shows how to do random erasing/cut out augmentation in CNN classification. random erasing や cut outとよばれる方法を用いて画像にマスクをかけ、分類を行います。

downloadCIFARToFolders(pwd);endThe cifar10 images were stored in the imagedatastore. A portion of training dataset was used for validation image.cd('cifar10')imds =

This function creates two cell arrays, one with training data and the other with testing data.

at random by turning shuffle 'on' or 'off'.The input data must be in column vectors/matrices, if the function believes you have entered a row vector/matrices it will automatically transpose the data

This demo shows how to detect the crack images using one-class SVM. このデモでは、1クラスSVMを用いて、ひび割れを自動的に検知します。

, 'LabelSource','foldernames');% split all the images into training, validation and test data [imdsTrain,imdsValid,imdsTest]=splitEachLabel(imds,0.7,0.1);% specify the image augmenter to implement image augmentationaugmenter =

Matlab-based software for measuring acoustic parameters and experiments.

in the Higher Polytechnic School of Gandia which is part of the Polytechnic University of Valencia, mainly giving access to equipment and instrumentation and data to be able to validate the results.The

CNN regression tool built to identify optimal network parameters using cross validation, includes image augmentation and random oversampling

Deep learning convolutional neural network regressionWith network parameter gridsearch, input normalization and geometric image augmenation:Network is designed to learn to predict a numerical value

spider_plot

version 18.1

by Moses

Create a spider or radar plot with customizable individual axes.

with most MATLAB versions.spider_plot_R2019b() is compatible with R2019b and above. It uses the new argument validation feature.spider_plot_class() is compatible with R2019b and above. It uses the new

This demo shows how to perform a data augmentation method called mix-up/random paring for image classification using CNN

. net=eval(netName);imgSize=net.Layers(1,1).InputSize;[imdsTrain,imdsValidation,imdsTest] = splitEachLabel(imds,0.7,0.1,'randomized');% readAndPreproc is a helper function to resize the input image so that the% images can be fed into the pre-trained network% augmentDatastore can replace

This example show how to classify images with imbalanced training dataset where the number of images per class is different over classes. 深

countEachLabel(imdsTrain)LabelCount1caesar_salad2392caprese_salad2393french_fries2394greek_salad2395hamburger2396hot_dog2397pizza2398sashimi2399sushi239histogram(imdsTrain.Labels)Load the pre-trained model, ResNet-18net = resnet18;inputSize = net.Layers(1).InputSize;lgraph = layerGraph(net);learnableLayer='fc1000';classLayer='ClassificationLayer_predictions';Modify the network

An app for exploring the predictions of an image classification network using several deep learning visualization techniques.

trained network called net and a validation image datastore called imdsVal, you can easily open the app to explore the trained network.UNPIC(net,imdsVal);This app is created for use with a DAG or series

Two files are provided: xgboost_train and xgboost_test which call the xgboost dll from inside Matlab. The example is for classification.

max_num_iters, without internal cross validation.Your own "outside" cross validation procedure can be used, which calls xgboost_train.m. An example of such outside procedure is documented in xgboost_train.mThe

Additional validator functions for Matlab

Fatigue damage accumulation for variable amplitude stress-time histories using the Palmgren-Miner rule.

, 1);% basic example (uses default values)% the first input is the stress-time history% the second input is the detail category (see EN 1993-1-9)damage = fatdamage(history, 160)% specify the number of

EDSR (Enhanced Deep Super-Resolution) Single Image Super Resolution Matlab port

file ■Input image MyPicture.jpg should be pristine (not blurred) image. EDSR neural net will upscale the image by 2x.img = imread("MyPicture.jpg"); % 1024x768 input image imgSR =

mex Lowtran7

version 1.0.0

by Meg Noah

mex version of Lowtran7 original fortran code

A very lean, simple script to run Lowtran7. Uses matlab mex utilities. Pass input and output filenames from matlab to Lowtran7. The scripts for creating TAPE5 are annotated and include validators

Simulink Transfer Function with Coefficients Input

These simulink blocks allow to input the transfer function its coefficients for the first, second and third order systems. This is beneficial for time varying parameters systems. The idea is simple

TCP/IP server and client for Matlab

A simulink sumulation of a novel DC DC converter with gain of 21 times.

mechanisms, the voltage stress on the switches and diodes are reduced. Moreover, due to the IBC in Stage 1, the current ripple content at the input side is reduced. To validate the proposed concept, simulation

Tool usable for simulating the pressure and temperature behavior within a district heating system.

Here a tool usable for simulating district heating systems. Giving as input some pipes network properties like nodes position, network topology, diameters, etc. it will provide the trend of the

A code that automatically computes the required number of plates, optimal feed plate, and minimum number of plates at Const. Rel. Volatility

System: Binary Design method: McCabe-ThieleCondition: Distillation with Constant Relative VolatilityRequired User inputs:-Feed amount (in mol)-Mole fraction of More Volatile Component (MVC) in Feed

Agent based simulation framework to validate planners in automated driving synthetic scenarios. The example demonstrates overtake maneuver.

environment.This demo showcases a Simulink model architecture for creating and simulating synthetic scenarios. It reads as input the scenario file saved using the Driving Scenario Designer (DSD) application. This

Project page of the paper "Learning Multi-Scale Photo Exposure Correction" (CVPR 2021).

:- exposure_dataset/ training/ INPUT_IMAGES/ GT_IMAGES/ validation/ INPUT_IMAGES/ GT_IMAGES/The src/patches_extraction.m will create subdirectories

LiquidAirPlant

version 1.0.2

by Sam Yang

LiquidAirPlant is a MATLAB code allowing its users to model various liquid air power plant configurations.

. Applied energy, 194, pp.522-529.which were referenced as validation cases for the proposed modeling framework.You can also rundriverto simulate a solar-driven LAPP as described in my paper.Model

DeepESN

version 1.1.2

by Claudio Gallicchio

DeepESN2019a: Deep Echo State Network (DeepESN) Toolbox v1.1.2

Memory Capacity (MC) task. - example_task_MC.m: The file contains an example of the usage of the methods in the Task class, including loading of (input and target) data from .csv files, and hold-out

This model is based on Simscape Electrical modeling of the power flow in an EV. In this project, three modeling styles are used to describe

describe the power flow model.Single model/Model reference/System ComposerThis model is very simple and should be able to be used for validation of requirement specifications and system

HRViewer

version 1.0.0

by Anurak Thungtong

HRViewer is a matlab software tool designed for in deep viewing and comparing HRV indices computed from different EKG files as well as diffe

An algorithm to parameterize volumetric shapes of the placenta represented as tetrahedral meshes to a flattened template.

toolboxmedical imaging MATLAB toolbox (only needed if working with NIFTI files)Add the MATLAB packages to the working path.Usagemain(grayImage, segImage): input a grayscale MRI image and the corresponding binary

Easy to use variable lenght input parameter parser mechanism with validation.

MLS package: To be able to install this library as an MLS package, you have to download it from GitHub as an MLS package: https://github.com/tiborsimon/simple-input-parser/releases/latestEasy to use

This code is used to interval uncertainty analysis based on Chebyshev interval inclusion function proposed by Jinglai Wu.

% function [y_lb,y_ub]=CI_reg(fun_name,a,b,k,K,Expansion)% Input% fun_name the called function name% a the lower bound vector of interval input % b the upper bound vector of interval input% k the

Gratuity Calculator for Indian Monthly Salaried Employees

Three control strategies for behind the meter residential batteries (Paper Link: https://ieeexplore.ieee.org/document/9638038).

more details and guidance on how to use the code.This tool was validated and detailed in the following published paper, please acknowledge any contributions of the RBMT by citing:[1]. A. A. R. Mohamed, R

Perform an online tuning of a proportional-integral (PI) speed controller for a servo DC motor using the Closed-Loop PID Autotuner block.

for a servo DC motor. The controller is validated using the Quanser QLabs Virtual QUBE-Servo 2, which is the digital twin of a physical Quanser QUBE-Servo 2. This submission originally apeared as a blog

simple_JsonDecode

version 1.2

by L Pir

Decodes a Json-file and returns a MATLAB-struct, suited for oder MATLAB versions (<2017)

for selecting a json fileInput: jsonFilePath: full path of json file Output: MATLAB-structAssumed format of json-file: "FIELDNAME1": DOUBLE, "FIELDNAME2": "STRING", "FIELDNAME3

System identification and LQR control design of the Quanser Rotary Flexible Link.

gage through the Quanser Q2-USB data acquisition (DAQ) device. The QUARC Bias Removal block removes any initial offset in the strain gage measurement. The voltage input, servo angle, and flexible link

leave-one-out crossvalidated linear regression

[PearsonR, PearsonP, SpearmanR, SpearmanP, yhat, R2 ] = BenStuff_CrossValCorr( x,y, [MathMagic], [OmNullModel] ) leave-one-out cross-validated simple linear regression INPUT VARIABLES: x, y

A toolbox for LAI validation and correction

The TSF toolbox was created based on the LAI validation and correction process in this thesis. Generally, it can preprocess LAI data worldwide by inputting required data (LAI, FparLai_Qc, FparEx_Qc

CO2SYS software for MATLAB (or GNU Octave) to calculate marine CO2 system variables and propagate uncertainties.

Version 3 of CO2SYS for MATLAB now accepts inputs of carbonate ion, bicarbonate, dissolved CO2, ammonium, and hydrogen sulfide. Choices for KSO4 constant, KF constant (Perez and Fraga (1987) has been

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