Results for: symbolic toolbox matlab

Seamlessly integrate COMSOL Multiphysics® with MATLAB® to extend your modeling with scripting programming in the MATLAB environment. LiveLink™ for MATLAB® allows you to utilize the full power of MATLAB and its toolboxes in preprocessing, model manipulation, and postprocessing. Enhance your in-house MATLAB code with powerful multiphysics simulations. Base your geometry modeling on probabilistic or image data.

MATLAB® combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, rigorously tested, and fully documented.

...DataMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. Linear, non-linear and symbolic regression are also available. Neural networks and various data-manipulation methods are integrated using Java API. Elements of symbolic computations using Octave/Matlab scripting are supported. DataMelt is a computational environment for Java platform. It can be used with different programming languages on different operating systems. ...

Model Predictive Control Toolbox™ provides functions, an app, Simulink® blocks, and reference examples for developing model predictive control (MPC). For linear problems, the toolbox supports the design of implicit, explicit, adaptive, and gain-scheduled MPC. For nonlinear problems, you can implement single- and multi-stage nonlinear MPC. The toolbox provides deployable optimization solvers and also enables you to use a custom solver.

...Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. MatConvNet is a MATLAB toolbox implementing Convolutional Neural Networks (CNNs) for computer vision applications. It is simple, efficient, and can run and learn state-of-the-art CNNs. Many pre-trained CNNs for image classification, segmentation, face recognition, and text detection are available.

...The new version includes many new functions such as topographic plots, CCA, new filters, an importer for cortiQ files, updates for Result2D, Cortio-Cortical Evoked Potentials, an ECoG toolbox, a TMS toolbox, and more! The package comes with many sample biosignal data sets, including P300, SSVEP, motor imagery, CSP BCIs, Tilt-Table, EPs, multi-unit activity, CFM, CCEP, and ERD/ERS. Interactive and intuitive graphical user interface for EEG, ECoG, EOG, EMG, ECG, spikes, and physical data analyses and documentation under MATLAB.

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