On the identification of FIR systems with binary input and output observations

Abstract

This paper considers the identification of FIR systems, where the inputs and outputs of the system undergoes quantization into binary values before transmission to the system identifier. Provided that the thresholds of the input and output quantizers can be adapted, we propose identification schemes which are strongly consistent for Gaussian distributed inputs and noises. Identification schemes are given both for the case where the mean and variance of the input distribution are known, and when they are unknown.