Interfacing PDM MEMS Microphones with PFM Spiking Systems: Application for Neuromorphic Auditory Sensors

Neuromorphic computation processes sensors output in the spiking domain, which presents constraints in many cases when converting information to spikes, loosing, as example, temporal accuracy. This paper presents a spike-based system to adapt audio information from low-power pulse-density modulation (PDM) microelectromechanical systems microphones into rate coded spike frequencies. These spikes could be directly used by the neuromorphic auditory sensor (NAS) for frequency decomposition in different bands, avoiding the analog or digital conversion to spike streams. This improves the time response of the NAS, allowing its use in more time restrictive applications. This adaptation was conducted in VHDL as an interface for PDM microphones, converting their pulses into temporal distributed spikes following a pulse-frequency modulation scheme with an accurate inter-spike-interval, known as PDM to spikes interface (PSI). We introduce a new architecture of spike-based band-pass filter to reject DC components and distribute spikes in time. This was tested in two scenarios, first as a stand-alone circuit for its characterization, and then integrated with a NAS for verification. The PSI achieves a total harmonic distortion of -46.18 dB and a signal-to-noise ratio of 63.47 dB, demands less than 1% of the resources of a Spartan-6 FPGA and its power consumption is around 7 mW.