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  • Real-Time Simulation and Testing with Simulink and Speedgoat

    In this blog and inserted video, recorded at the SciEngineering Conference 2022, we delve deeper into the world of Rapid Control Prototyping (RCP) and Hardware-in-the-Loop (HIL) testing and how RCP and HIL testing can be utilized to detect design flaws early in the development process.

  • Ai robotics working on a car

    AI: Driving the Industry Towards Greater Success

    Artificial intelligence (AI) is seen as a promising technology that can help leading OEMs to maintain their position as market leaders. In this post, read about how AI is changing the manufacturing sector, as well as its potential advantages and potential drawbacks.

  • MATLAB and Simulink for Artificial Intelligence

    Learn about MATLAB and Simulink’s capabilities for creating AI-driven products and services, including the benefits of using these platforms, key components of the AI workflow, and the integration of AI models into real-world applications.

  • Excitation Signals for Identification of Dynamic Systems

    Excitation Signals for Identification of Dynamic Systems

    Learn about optimizing multisine signals for precise frequency-domain system identification. Discover the importance of low Crest Factor (CF) in excitation signals and explore techniques to enhance signal-to-noise ratios (SNR) for improved measurement accuracy.

  • Motor Control Design with Simulink

    Learn how to reduce motor control development time by using simulation models to design and verify control algorithms and deploy those algorithms to hardware using automatic code generation.

  • Deep Learning for Images Classification

    Learn about image classification and why it’s crucial in computer vision. Discover how deep learning techniques can revolutionize image recognition, automate tasks, and enhance various applications like visual inspection, automated driving, and robotics. Dive into the realm of visual AI with deep learning and MATLAB.