Introduction
This project aims to develop a Cube AI application for the STM32 microcontroller that generates a sine wave using a fully connected neural network and transmits it through UART. The STM32 microcontroller, known for its high performance and low power consumption, is an ideal platform for implementing AI-based applications. By leveraging the capabilities of Cube AI, we can efficiently deploy a neural network on the microcontroller to generate a sine wave, which is a fundamental waveform in signal processing and communication systems.
The neural network is trained to approximate the sine function, and its implementation on the STM32 ensures real-time generation of the waveform. The generated sine wave is then transmitted via UART, a widely used serial communication protocol, enabling seamless integration with other devices and systems. This project demonstrates the potential of combining AI with embedded systems to perform complex tasks with high efficiency and accuracy.
Digi key tutorial - https://www.youtube.com/watch?v=crJcDqIUbP4 collab notebook - https://gist.github.com/ShawnHymel/79237fe6aee5a3653c497d879f746c0c My implementation of the ML model - https://www.youtube.com/watch?v=FATDq8oJkOM