MathWorks MATLAB and Simulink Release 2020a

Friday, 08 May, 2020 | Supplied by: MathWorks Australia

MathWorks has introduced Release 2020a of MATLAB and Simulink, with expanded AI capabilities for deep learning. Engineers can now train neural networks in the updated Deep Network Designer app, manage multiple deep learning experiments in the Experiment Manager app and choose from more network options to generate deep learning code. R2020a introduces capabilities specifically for automotive and wireless engineers in addition to hundreds of features for all users of MATLAB and Simulink.

The release introduces an enhanced Deep Learning Toolbox that helps users manage multiple deep learning experiments, keep track of training parameters, and analyse and compare results and code with the Experiment Manager app. Users can also interactively train a network for image classification, generate MATLAB code for training and access pre-trained models with Deep Network Designer app. Additionally, GPU Coder now offers a more expansive set of networks to implement AI systems on cloud and edge devices, including Darknet-19, Darknet-53, Inception-ResNet-v2, NASNet-Large and NASNet-Mobile.

Motor Control Blockset contains a library of motor control algorithms optimised for generating compact code as well as out-of-the-box support for multiple motor control hardware kits. Simulink Compiler lets engineers generate standalone applications, web apps and software components from Simulink models, enabling simulations to run without installing Simulink. MATLAB Web App Server offers controlled access from a browser to MATLAB web apps deployed across a user’s organisation.

The latest updates mean automotive engineers can more easily create driving scenarios using imported road data from high-definition geographic maps and optimise shift schedules for performance, fuel economy and emissions analysis. For wireless engineers, MATLAB support for 5G and Wi-Fi 6 technologies has expanded with additional support for waveform generation and cell detection. Users can also generate C++ classes from MATLAB classes, and the release introduces message-based communication for service functions and re-usable subsystems.

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