Linear systems identification from random threshold binary data

A new identification problem of estimating parameters of linear dynamic 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 inst...

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Bibliographic Details
Published in:IEEE transactions on signal processing 1996-08, Vol.44 (8), p.2064-2070
Main Author: Rafajlowicz, E.
Format: Article
Language:English
Subjects:
Applied sciences
Computer science
control theory
systems
Control theory. Systems
Exact sciences and technology
Linear systems
Modelling and identification
Noise measurement
Parameter estimation
Random number generation
Remote sensing
Signal processing
Sonar applications
Sonar measurements
State estimation
System identification
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Summary:A new identification problem of estimating parameters of linear dynamic 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 mainly for generating random numbers. Strong consistency of parameters estimate from low-cost output binary observations is proved, assuming deterministic input signal of a finite duration. Possibilities of relaxing the assumption used in the theoretical part of the paper are considered by means of simulations.
ISSN:1053-587X
1941-0476
DOI:10.1109/78.533726