This paper reports a spatial extrapolation of the sound field with a physics-informed neural network. We investigate the spatial extrapolation of the room impulse responses with physics-informed SIREN architecture. Furthermore, we proposed a noise-robust extrapolation method by introducing a tolerance term to the loss function.

A new digital calibration scheme for a 14 bit binary weighted current-steering digital-to-analog converter (DAC) is presented. This scheme uses a simple current comparator for the current measurement instead of a high-resolution ADC. Therefore, a faster calibration cycle and smaller additional circuits are possible compared to the scheme with the high-resolution ADC. In the proposed calibration scheme, the lowest 8 bit part of the DAC is used for both error correction and normal operation. Therefore, the extra DACs required for calibration are only a 3 bit DAC and a 6 bit DAC. Nevertheless, a large calibration range is achieved. Full 14 bit resolution is achieved with a small chip-area. The simulation results show that DNL and INL after calibration are 0.26 LSB and 0.46 LSB, respectively. They also show that the spurious free dynamic range is 83 dB (57 dB) for signals of 24 kHz (98 MHz) at 200 Msps update rate.