Journal article

Identification of fir systems with binary input and output observations

AS Leong, E Weyer, GN Nair

IEEE Transactions on Automatic Control | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2021

DOI: 10.1109/TAC.2020.3042478

Abstract

This article considers the identification of finite-impulse response systems, where information about the inputs and outputs of the system undergoes quantization into binary values before transmission to the estimator. In the case where the thresholds of the input and output quantizers can be adapted, we propose identification schemes that are strongly consistent for Gaussian distributed inputs and noises. The algorithms are based on the idea that certain joint probabilities of the unquantized signals can be estimated from the binary signals, and the system parameters can then be inferred from these estimates. The algorithms and their properties are illustrated in simulation examples.

University of Melbourne Researchers

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Keywords

Stochastic Processes
Engineering
Binary Measurements
Parameter Estimation
Random Variables
Standards
Pollution Measurement
Science & Technology
4007 Control Engineering, Mechatronics and Robotics
Fir Systems
Automation & Control Systems
Finite Impulse Response Filters
Data Models
System Identification
Engineering, Electrical & Electronic
Technology
Rivers
40 Engineering