State estimation with point and set measurements
Numerous state estimation problems (eg, under linear or nonlinear inequality constraints,
with quantized measurements) can be formulated as those with point and set
measurements. Inspired by the estimation with quantized measurements developed by
Curry, under a Gaussian assumption, the minimum mean-squared error (MMSE) filtering
with point measurements and set measurements of any shape is proposed by discretizing
continuous set measurements. Possible ways to relax the Gaussian assumption and to …
with quantized measurements) can be formulated as those with point and set
measurements. Inspired by the estimation with quantized measurements developed by
Curry, under a Gaussian assumption, the minimum mean-squared error (MMSE) filtering
with point measurements and set measurements of any shape is proposed by discretizing
continuous set measurements. Possible ways to relax the Gaussian assumption and to …
[PDF][PDF] State Estimation with Point and Set Measurements
ZDXRL Vesselin, P Jilkov - researchgate.net
Numerous state estimation problems (eg, under linear or nonlinear inequality constraints,
with quantized measurements) can be formulated as those with point and set
measurements. Inspired by the estimation with quantized measurements developed by
Curry [1], under a Gaussian assumption, the minimum mean-squared error (MMSE) filtering
with point measurements and set measurements of any shape is proposed by discretizing
continuous set measurements. Possible ways to relax the Gaussian assumption and to …
with quantized measurements) can be formulated as those with point and set
measurements. Inspired by the estimation with quantized measurements developed by
Curry [1], under a Gaussian assumption, the minimum mean-squared error (MMSE) filtering
with point measurements and set measurements of any shape is proposed by discretizing
continuous set measurements. Possible ways to relax the Gaussian assumption and to …
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