MathWorks’ Release 2019a of MATLAB and Simulink Brings AI to Its Popular Software Environment

May 1, 2019 Rich Nass

If you were waiting for AI enhancements to MATLAB and Simulink, your wait is over. Mathworks recently released version 2019a of its popular software. According to the company, with R2019a, engineers can extend their AI skills to develop controllers and decision-making systems using reinforcement learning, training deep learning models on NVIDIA DGX and cloud platforms, or applying deep learning to 3D data.

R2019a introduces Reinforcement Learning Toolbox, further enhancing the MATLAB workflow for AI. The toolbox facilitates a type of machine learning that trains an “agent” through repeated trial-and-error interactions with an environment to solve controls and decision-making problems.

R2019a, which is available now, features several new signal processing and communications products to support wireless and electronics development, including three Simulink add-ons: Mixed-Signal Blockset, which provides fast model construction, rapid simulation, and deep insights into mixed-signal system design models with dedicated analysis and visualization tools; SerDes Toolbox, which offers the SerDes Designer app for rapid design, analysis, and modeling of wired communications transmitters and receivers; and SoC Blockset, which enables simulation and exploration of FPGA, ASIC and SoC architectures, co-simulation of algorithms and hardware platforms, and performance monitoring and bottleneck detection.

About the Author

Rich Nass

Richard Nass is the Executive Vice-President of OpenSystems Media. His key responsibilities include setting the direction for all aspects of OpenSystems Media’s Embedded and IoT product portfolios, including web sites, e-newsletters, print and digital magazines, and various other digital and print activities. He was instrumental in developing the company's on-line educational portal, Embedded University. Previously, Nass was the Brand Director for UBM’s award-winning Design News property. Prior to that, he led the content team for UBM Canon’s Medical Devices Group, as well all custom properties and events in the U.S., Europe, and Asia. Nass has been in the engineering OEM industry for more than 25 years. In prior stints, he led the Content Team at EE Times, handling the Embedded and Custom groups and the TechOnline DesignLine network of design engineering web sites. Nass holds a BSEE degree from the New Jersey Institute of Technology.

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