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Spectrum Analyzer using FFT running on Raspberry Pi Pico 2
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Here is a demo of the Fast Fourier Transform (FFT) algorithm running on the Raspberry Pi Pico 2. The FFT has a size of 256 and it runs in around 17 milliseconds. The FFT is written in ARM assembler using Peter Hinch's library. The display is a 128x64 2.42" OLED with the SSD1306 driver and the microphone is an INMP445 running over I2S at 8K samples per second.
Performance Statistics (average over 100 cycles):
- Audio capture time: 16.49 ms (21.7%)
- FFT processing time: 17.23 ms (22.6%)
- Display update time: 42.40 ms (55.7%)
- Total cycle time: 76.13 ms
- Theoretical max FPS: 13.1
The documentation is on my "Learning MicroPython" site here:
I have not tried to increase the speed of the OLED by changing the baud parameter yet.
Performance Statistics (average over 100 cycles):
- Audio capture time: 16.49 ms (21.7%)
- FFT processing time: 17.23 ms (22.6%)
- Display update time: 42.40 ms (55.7%)
- Total cycle time: 76.13 ms
- Theoretical max FPS: 13.1
The documentation is on my "Learning MicroPython" site here:
I have not tried to increase the speed of the OLED by changing the baud parameter yet.
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Spectrum Analyzer using FFT running on Raspberry Pi Pico 2
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