Sự Kiện

Attend this session if you are developing or researching autonomous UAV and are interested in how scenario simulations can help evaluate your autonomous flight algorithms.

In this session you will learn the basics of simulating physical systems in Simscape. The physical network approach in Simscape enables you to model physical systems by simply assembling a schematic of physical components.

Join us in this panel discussion where leaders who work with startups, researchers, corporations, startups themselves and policymakers working towards climate action discuss the role of innovation in tackling climate change.

In this session we will show how you can bring your digital health applications from MATLAB to the cloud, starting from web applications for internal use to professional and scalable enterprise platforms.

In this webinar, you will learn how to empower your robots using deep learning and reinforcement learning for perception and motion control in autonomous robotics applications including robot manipulators, autonomous mobile robots, and UAVs using MATLAB.

Deep learning and machine learning techniques can be applied to a range of radar and wireless applications to meet the increased level of system requirements of operating in a crowded RF spectrum.

MATLAB provides flexible, two-way integration with many programming languages, including Python. This allows different teams to work together and use MATLAB algorithms within production software and IT systems. This webinar will cover how to call MATLAB from Python and how to call Python libraries from MATLAB.

In this webinar, we will demonstrate a real-world medical application of an ECG analysis and show how you can use MATLAB & Simulink to train and verify AI models. You will learn some basic and advanced techniques in order to fully utilize the benefits of machine learning in biomedical signal analysis.

In this presentation, Heng Chen from HSBC takes a deep technical dive into extreme value theory and parametric modelling techniques to estimate Value at Risk at high quantiles.