Deep Learning
Extend deep learning workflows on STM32 processors for computer
vision, image processing, signals, audio, and text analytics
Use Deep Learning Toolbox™ to incorporate deep learning in computer vision, image processing, signal processing, audio, and text analytics applications.
Topics
- Building Neural Network for Virtual Position Sensing
Build a neural network for virtual position sensing.
Featured Examples
Field-Oriented Control of PMSM Using Position Estimated by Neural Network on STM32 Processor Based Boards
Implement field-oriented control (FOC) of a permanent magnet synchronous motor (PMSM) using rotor position estimated by an auto-regressive neural network (ARNN) trained with Deep Learning Toolbox™.
Recognize Handwritten Digits Zero to Nine Using MNIST Data Set on STM32 Processor Boards
Use STM32™ Microcontroller Blockset to recognize digits from zero to nine. The algorithm used in this example recognizes the digits and then outputs a label for the digit.
