Identification for FIR Systems With Scheduled Binary-Valued Observations

This paper studies the identification of finite impulse response (FIR) systems whose output observations are subject to both the binary-valued quantization and the scheduling scheme. By utilizing the statistical property of the system noise and the scheduling policy, an empirical-measure-based identification algorithm is proposed. Under periodical inputs, it is proved that the estimation from the algorithm can converge to the real parameters. The mean-square convergence rate of the estimation error is established, based on which and the Cramér-Rao lower bound, the asymptotic efficiency of algorithm is proved. Moreover, the communication rate is derived and the input design problem is discussed. A numerical example is given to illustrate the main results obtained.

• Publication year

  2018

• Venue

  IEEE Access

• Publication date

  Unknown publication date

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1109/ACCESS.2018.2851302
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Hybrid Scheduling and Quantized Output Feedback Control for Networked Control Systems

  2018cited by this paper
• Transmission scheduling for remote state estimation and control with an energy harvesting sensor

  2018cited by this paper
• A multi-channel transmission schedule for remote state estimation under DoS attacks

  2017cited by this paper
• Error-dependent data scheduling in resource-aware multi-loop networked control systems

  2017cited by this paper
• Identification of Wiener systems with quantized inputs and binary-valued output observations

  2017cited by this paper
• Optimal communication scheduling and remote estimation over an additive noise channel

  2016cited by this paper
• Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs

  2015cited by this paper
• Optimal Parameter Estimation Under Controlled Communication Over Sensor Networks

  2015cited by this paper
• Stochastic packet scheduling for optimal parameter estimation

  2015cited by this paper
• Asymptotically Optimal Parameter Estimation With Scheduled Measurements

  2013cited by this paper
• System Identification Using Regular and Quantized Observations: Applications of Large Deviations Principles

  2013cited by this paper
• Fixed-order FIR approximation of linear systems from quantized input and output data

  2013cited by this paper
• Input Design in Worst-Case System Identification Using Binary Sensors

  2011cited by this paper
• Asymptotically optimal parameter estimation under communication constraints

  2011cited by this paper
• A Weighted Least-Squares Approach to Parameter Estimation Problems Based on Binary Measurements

  2010cited by this paper
• System Identification with Quantized Observations

  2010cited by this paper
• Identification of Hammerstein Systems with Quantized Observations

  2010cited by this paper
• A Survey of Recent Results in Networked Control Systems

  2007cited by this paper
• System identification using binary sensors

  2003cited by this paper
• Sensor Networks

  2002cited by this paper
• Author's Personal Copy Identification of Wiener Systems with Binary-valued Output Observations ଁ

  year unknowncited by this paper

• No citing papers are available for this paper.