This support package enables you to deploy a deep learning processor on Intel® FPGA and SoC based hardware from MATLAB

Debug and test HDL code on Microchip FPGAs using FPGA-in-the-loop

Generate code optimized for Infineon AURIX TC4x Microcontrollers

Control instruments using Rohde & Schwarz VISA (R&SVISA)

Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0

A toolbox to encode/decode JSON and UBJSON files in MATLAB/Octave

A collection of standard drive cycles (vehicle speed vs. time)

A collection of standard drive cycles and maneuvers

Land cover basemap data for geographic visualization

Gray land, white water basemap data for geographic visualization

Tools to compile a real-time application that runs on a Speedgoat target computer

Gray terrain basemap data for geographic visualization

Import, visualize, process, analyze and export hyperspectral data

Verify and test robustness of deep learning networks, deploy with confidence

Generate testbenches for ASIC and advanced FPGA designs

Build, Simulate, and Run Quantum Algorithms

Pretrained GoogLeNet network trained on Places365 data set for image classification

Pretrained EfficientNet-b0 model for image classification