Multichannel time-encoding using the integrate-and-fire model enables perfect reconstruction of finite-rate-of-innovation signals with reduced sampling requirements compared to single channel cases.
The study proposes a method for multichannel time-encoding that allows perfect reconstruction of finite-rate-of-innovation signals with reduced sampling requirements.
Time-encoding of continuous-time signals is an alternative sampling paradigm to Shannon sampling. In time-encoding or event-driven sampling, the signal is encoded using a sequence of time instants corresponding to an event. In this paper, we propose multichannel time-encoding of signals with a finite-rate-of-innovation (FRI) in single-input-multi-output (SIMO) and multi-input-multi-output (MIMO) configurations using the integrate-and-fire model. We demonstrate perfect reconstruction of FRI signals with common support from MIMO time-encoded measurements using a joint estimation technique, and perfect reconstruction of FRI signals from SIMO time-encoded measurements with reduced sampling requirement as compared to the single channel case. We provide sufficient conditions for perfect reconstruction with sampling requirement of the order of the rate of innovation of the signal. We substantiate our claims using simulations on noise-free and noisy measurements.
Kamath et al. (Fri,) conducted a other in Finite-Rate-of-Innovation (FRI) signals. Multichannel time-encoding in SIMO and MIMO configurations using the integrate-and-fire model vs. Single channel case / Shannon sampling was evaluated on Perfect reconstruction of FRI signals. Multichannel time-encoding using the integrate-and-fire model enables perfect reconstruction of finite-rate-of-innovation signals with reduced sampling requirements compared to single channel cases.