I'm also curious about the power draw of continuously executing FFTs on a rpi.
Seems like the kind of task where one could easily burn 10 watts, if the wrong FFT Implementation is chosen. You'd absolutely want to do this in DSP hardware.
Seems like the kind of task where one could easily burn 10 watts, if the wrong FFT Implementation is chosen. You'd absolutely want to do this in DSP hardware.
For reference, it eats ~25% of the available CPU resources on my rpi zero 2w - which draws a maximum of 350mA, so this implementation definitely draws less than 1 watt.
maybe could try pyfda and the filtering functions in scipy.signal to start playing around.
or if you have access to matlab it has some really excellent filter design tools.
regarding the hardware/dsp: many cpus include simd instructions these days, which basically are an interface to a hidden digital signal coprocessor. :)