Optimal Prediction of Unmeasured Output from Measurable Outputs In LTI Systems

09/06/2021

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In this short article, we showcase the derivation of an optimal predictor, when one part of system's output is not measured but is able to be predicted from the rest of the system's output which is measured. According to author's knowledge, similar derivations have been done before but not in state-space representation.

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Optimal Prediction of Unmeasured Output from Measurable Outputs In LTI Systems

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Output-Dependent Gaussian Process State-Space Model

Measured Multiseries and Integration

Accelerating Kinodynamic RRT* Through Dimensionality Reduction

Impact of predictor measurement heterogeneity across settings on performance of prediction models: a measurement error perspective

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Optimal Prediction of Unmeasured Output from Measurable Outputs In LTI Systems

Related Research

Deep KKL: Data-driven Output Prediction for Non-Linear Systems

Output-Dependent Gaussian Process State-Space Model

Measured Multiseries and Integration

Accelerating Kinodynamic RRT* Through Dimensionality Reduction

Impact of predictor measurement heterogeneity across settings on performance of prediction models: a measurement error perspective

Harmonization and the Worst Scanner Syndrome

A note on the article "On Exploiting Spectral Properties for Solving MDP with Large State Space"