Sequential Source Coding for Stochastic Systems Subject to Finite Rate Constraints
In this paper, we revisit the sequential source coding framework to analyze fundamental performance limitations of discrete-time stochastic control systems subject to feedback data-rate constraints in finite-time horizon. The basis of our results is a new characterization of the lower bound on the m...
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Main Authors | , , |
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Format | Journal Article |
Language | English |
Published |
10.06.2019
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Subjects | |
Online Access | Get full text |
DOI | 10.48550/arxiv.1906.04217 |
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Summary: | In this paper, we revisit the sequential source coding framework to analyze
fundamental performance limitations of discrete-time stochastic control systems
subject to feedback data-rate constraints in finite-time horizon. The basis of
our results is a new characterization of the lower bound on the minimum
total-rate achieved by sequential codes subject to a total (across time)
distortion constraint and a computational algorithm that allocates optimally
the rate-distortion for any fixed finite-time horizon. This characterization
facilitates the derivation of analytical, non-asymptotic, and
finite-dimensional lower and upper bounds in two control-related scenarios. (a)
A parallel time-varying Gauss-Markov process with identically distributed
spatial components that is quantized and transmitted through a noiseless
channel to a minimum mean-squared error (MMSE) decoder. (b) A time-varying
quantized LQG closed-loop control system, with identically distributed spatial
components and with a random data-rate allocation. Our non-asymptotic lower
bound on the quantized LQG control problem, reveals the absolute minimum
data-rates for (mean square) stability of our time-varying plant for any fixed
finite time horizon. We supplement our framework with illustrative simulation
experiments. |
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DOI: | 10.48550/arxiv.1906.04217 |