Search Results for "matlab optimization toolbox"
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Showing 36 open source projects for "matlab optimization toolbox"
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Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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PlatEMO
Evolutionary multi-objective optimization platform
Evolutionary multi-objective optimization platform. PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. -
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Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
The Grey Wolf Optimizer for Path Planning is a MATLAB-based implementation of the Grey Wolf Optimizer (GWO) algorithm designed for UAV path and trajectory planning. It allows simulation of both two-dimensional and three-dimensional UAV trajectory planning depending on parameter setups. The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. -
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QuantumOptics.jl
Library for the numerical simulation of closed as well as open quantum
QuantumOptics.jl is a numerical framework written in the Julia programming language that makes it easy to simulate various kinds of open quantum systems. It is inspired by the Quantum Optics Toolbox for MATLAB and the Python framework QuTiP. QuantumOptics.jl optimizes processor usage and memory consumption by relying on different ways to store and work with operators. The framework comes with a plethora of pre-defined systems and interactions making it very easy to focus on the physics, not on the numerics. Every function in the framework has been severely tested with all tests and their code coverage presented on the framework's GitHub page. -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and... -
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CasADi
CasADi is a symbolic framework for numeric optimization
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT, etc. It can be used in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. ... -
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Optimizer_sovkov
Constructing and optimizing general mathematical and physical models
We present the package Optimizer, aimed at constructing and optimizing general mathematical models of phenomena of versatile nature. It is written in the Matlab algorithmic language and is executed in the Matlab environment with partial functionality in Octave. The convenient visual interface and the detailed manuals are provided. The main benefit of the package is its capability to construct models of any level of complexity in a block-by-block manner. Elementary model blocks can be collected in libraries, and we have already written many such library programs. ... -
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Continuation Core and Toolboxes (COCO)
Toolboxes for parameter continuation and bifurcation analysis.
Development platform and toolboxes for parameter continuation, e.g., bifurcation analysis of dynamical systems and constrained design optimization. This material is based upon work partially supported by the National Science Foundation under Grant No. 1016467 and the Danish research council (FTP) under the project number 0602-00753B. Any opinions, findings, and conclusions or recommendations expressed on this site are those of the authors and do not necessarily reflect the views of the... -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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MARRMoT
Modular Assessment of Rainfall-Runoff Models Toolbox
MARRMoT (Modular Assessment of Rainfall-Runoff Models Toolbox) is a MATLAB toolbox designed for hydrological modeling. It allows users to simulate and assess various rainfall-runoff models, providing tools for calibration, sensitivity analysis, and comparison of model performance. -
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OptimTraj
A trajectory optimization library for Matlab
OptimTraj is a MATLAB toolbox for solving trajectory optimization problems. It supports direct collocation, shooting methods, and pseudospectral methods for finding optimal control inputs and system trajectories. It is useful for robotics, aerospace, biomechanics, and any domain requiring time-optimal or energy-optimal motion planning. -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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Smart Algorithm
Repository implementing a variety of intelligent algorithms
...Immune Algorithm (or immune-inspired optimization) implementations. Multiple versions/language compatibility (Java, Python, MATLAB). -
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PRMLT
Matlab code of machine learning algorithms in book PRML
...It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). -
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Tensor Algebra Compiler
The Tensor Algebra Compiler (taco) computes sparse tensor expressions
...Under the hood, TACO employs a novel compiler-based technique to generate kernels that are optimized for the computations you want to perform. This lets TACO achieve performance that exceeds the MATLAB Tensor Toolbox by up to several orders of magnitude and that is competitive with other high-performance sparse linear/tensor algebra libraries like Eigen, Intel oneMKL, and SPLATT. -
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Kalibr Allan
IMU Allan standard deviation charts
kalibr_allan is a utility repository that provides scripts and tools for calculating IMU noise parameters for use in Kalibr and other IMU filtering systems. While manufacturers typically provide “white noise” values in IMU datasheets, the bias instability and random walk parameters must be determined experimentally. This project enables users to compute those values using Allan variance analysis from recorded IMU data. The workflow involves recording IMU measurements with the device... -
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ATLAS_mPBPK
Modeling and Simulation of mPBPK models
ATLAS mPBPK is a MATLAb-based tool for modeling and Simulation of minimal Physiology Based Pharmacokinetic (mPBPK) models of small and large molecules. The tool enables the users to perform: i) PK data visualization, ii) simulation, iii) parameter optimization, and iv) local sensitivity analysis (SA) of mPBPK models in a simple and efficient manner. -
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cocolib / light field suite
CUDA library for continuous optimization and light field analysis
Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface. Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs. Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms. *** NOTE: documentation on the SourceForge page is outdated and not updated anymore, please visit http://cocolib.net *** -
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CRFasRNN
Semantic image segmentation method described in the ICCV 2015 paper
CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps. Our work allows computers to recognize objects in images, what is distinctive about our work is that we also... -
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
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matImage
An image processing and analysis library for Matlab
MatImage is a Matlab library for image processing and analysis in 2D and 3D. It contains more than 250 fonctions for image enhancement, filtering, analysis, or visualisation, as well as for creating basic test shapes. It is built as a complement of the Mathworks image processing toolbox (IPT). Project is being transfered to GitHub: http://github.com/dlegland/matImage -
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BudgetedSVM
BudgetedSVM: A C++ Toolbox for Large-scale, Non-linear Classification
...We provide command-line and Matlab interfaces to BudgetedSVM, efficient API for handling large-scale, high-dimensional data sets, as well as detailed documentation to help developers use and further extend the toolbox. -
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Geospace Analysis Package
MatLab toolbox for magnetospheric and ionospheric science.
A MatLab toolbox with many simple and useful functions for analyzing data from Cluster, Champ and the Swarm missions. Other functions for space plasma physics, magnetospheric and ionospheric research are included. The toolbox is designed to be as simple as possible. Each function can be learned and used individually. See the tutorial in the Files section for a quick introduction. -
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SPE Toolbox
MatLab functions for reading WinView/WinSpec .spe files
This toolbox is a collection of MatLab functions for reading WinView/WinSpec files (.spe extension) directly to MatLab. It provides functions for reading full header from file into a structure, reading frames into matrices, and reading pixel values across all frames. You can use these functions to analyse and process experiment data stored in .spe files in MatLab, and to write functions to export .spe files to animated GIFs for use in presentations. -
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WM Hyperintensities Segmentation Toolbox
Open Source White Matter Hyperintensities Segmentation Toolbox
Wisconsin White Matter Hyperintensity Segmentation [W2MHS] and Quantification Toolbox is an open source MatLab toolbox designed for detecting and quantifying White Matter Hyperintensities (WMH) in Alzheimer’s and aging related neurological disorders. WMHs arise as bright regions on T2- weighted FLAIR images. They reflect comorbid neural injury or cerebral vascular disease burden. Their precise detection is of interest in Alzheimer’s disease (AD) with regard to its prognosis. ...
