Recursive identification of FIR systems with binary-valued outputs and communication channels
This paper investigates the recursive identification of the finite impulse response systems
whose outputs are subject to both the binary-valued quantization and the communication …
whose outputs are subject to both the binary-valued quantization and the communication …
A two-filter approach for state estimation utilizing quantized output data
Filtering and smoothing algorithms are key tools to develop decision-making strategies and
parameter identification techniques in different areas of research, such as economics …
parameter identification techniques in different areas of research, such as economics …
On Filtering and Smoothing Algorithms for Linear State-Space Models Having Quantized Output Data
The problem of state estimation of a linear, dynamical state-space system where the output
is subject to quantization is challenging and important in different areas of research, such as …
is subject to quantization is challenging and important in different areas of research, such as …
A numerical solution to the Bayesian tracking problem using statistical manifolds
D Marelli, D Li, M Fu, Q Cai, R Lu - Automatica, 2025 - Elsevier
In the general non-linear, non-Gaussian case, the Bayesian tracking formulas lack an
analytic expression. For this reason a number of numerical approximate solutions are …
analytic expression. For this reason a number of numerical approximate solutions are …
On filtering methods for state-space systems having binary output measurements
In this paper we develop two filtering algorithms for state-space systems with binary outputs.
We approximate the conditional probability mass function of the output signal given the state …
We approximate the conditional probability mass function of the output signal given the state …
EM-based identification of ARX systems having quantized output data
JC Agüero, K González, R Carvajal - IFAC-PapersOnLine, 2017 - Elsevier
ScienceDirect Page 1 IFAC PapersOnLine 50-1 (2017) 8367–8372 ScienceDirect Available
online at www.sciencedirect.com 2405-8963 © 2017, IFAC (International Federation of …
online at www.sciencedirect.com 2405-8963 © 2017, IFAC (International Federation of …
A novel approach to model error modelling using the expectation-maximization algorithm
In this paper we develop a novel approach to model error modelling. There are natural links
to others recently developed ideas. However, here we make several key departures, namely …
to others recently developed ideas. However, here we make several key departures, namely …
Estimation of general time-varying single particle tracking linear models using local likelihood
In this work, we study a general approach to the estimation of single particle tracking models
with time-varying parameters. The main idea is to use local Maximum Likelihood (ML) …
with time-varying parameters. The main idea is to use local Maximum Likelihood (ML) …
Incorporation of system steady state properties into subspace identification algorithm
Most of the industrial applications are multiple-input multiple-output (MIMO) systems that can
be identified using the knowledge of the system's physics or from measured data employing …
be identified using the knowledge of the system's physics or from measured data employing …
A novel bayesian filtering method for systems with quantized output data
R Albornoz, R Carvajal… - 2019 IEEE CHILEAN …, 2019 - ieeexplore.ieee.org
In this paper we develop a novel scheme for state estimation of discrete-time linear time-
invariant systems with quantized output data. We take a Bayesian approach, therefore, we …
invariant systems with quantized output data. We take a Bayesian approach, therefore, we …