flasonil/Deep-Neural-Network-for-CS-based-signal-reconstruction-on-STM32-MCU-board

Compressed Sensing signal decoding with DNN oracle on STM32

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Emerging

This project helps embedded systems engineers reconstruct high-fidelity signals from limited data using a neural network deployed on an STM32 microcontroller. It takes compressed signal measurements as input, processes them on the MCU, and outputs the reconstructed signal's sparse coefficients and the full signal, enabling efficient data acquisition. This is ideal for professionals working with resource-constrained devices in signal processing applications.

No commits in the last 6 months.

Use this if you need to perform compressed sensing signal reconstruction directly on an STM32 microcontroller, leveraging a pre-trained deep neural network for faster and more efficient decoding.

Not ideal if your application does not involve signal processing, compressed sensing, or the use of STM32 microcontrollers for embedded AI.

embedded-systems signal-processing microcontroller-programming real-time-analytics data-compression
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 13 / 25

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Stars

16

Forks

3

Language

Python

License

MIT

Last pushed

Apr 05, 2021

Commits (30d)

0

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