LINEAR-SYSTEMS IDENTIFICATION FROM RANDOM THRESHOLD BINARY DATA

A new identification problem of estimating parameters of linear dynami c systems from random threshold binary observations of its output and input is stated, The only available data are collected as a result of checking whether a signal reached a randomly specified threshold at a randomly chosen instant of time. The proposed estimation algorithm is based on the celebrated von Neumann theorem, which was earlier used ma inly for generating random numbers. Strong consistency of parameters e stimate from few-cost output binary observations is proved, assuming d eterministic input signal of a finite duration, Possibilities of relax ing the assumption used in the theoretical part of the paper are consi dered by means of simulations.