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In this session will learn how to model grid-tied inverter using Simulink and Simscape Electrical and perform power electronic simulation
Read MoreIn this session we will discuss state-of-the-art approaches for visual inspection and present multiple case studies on how these approaches have been applied in industry.
Read MoreWant to quickly and easily analyze UAV autopilot flight logs? Explore the Flight Log Analyzer Tool in MATLAB for customized plots and efficient analysis.
Read MoreThis webinar will provide a complete environment for the development of intelligent systems and the making of data-driven decisions. With MATLAB and Simulink, you can build models to use AI techniques such as deep learning, reinforcement learning, and evolutionary algorithms.
Read MoreThe need for advanced civil and defense systems has been brought into sharp focus. In civil, the drive for zero climate impact is driving development of advanced propulsion, autonomous systems, and urban...
Read MoreIn this webinar, you will learn about single- and multi-user MIMO in 5G NR, as well as common beamforming techniques and scenarios. We will cover different techniques to estimate the channel or channel...
Read MoreThis session demonstrates an end-to-end MATLAB workflow for developing anomaly detection models in the context of a pill production quality control data set comprising a large collection of images. The objective is to verify the quality of pills using automated visual inspection techniques.
Read MoreModel-Based Design affords many advantages over traditional development by offering high-level design abstractions and automatic generation of production code. Modeling and code generation for AUTOSAR software components lets you automate the process of specifying and synchronizing lengthy identifiers in designs
Read MoreThis presentation considers the alternative construction of the design space based on experiment data and a grey-box model of the reactions. The models are subsequently used to optimize the production process by changing the process variables. In addition, the effect of uncertainty and variability of the parameters on the process performance is also examined with a Monte-Carlo simulation.
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