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In this paper, the issue of an non-fragile filter design is addressed for a class of discrete-time singular Markovian jump systems subject to time-varying delay and missing measurements based on the extended passivity theory.
Genome Singapore identified the nearest-neighbors of missing measurements based on similarity of the measurement profiles [21].
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To obtain equidistant measurements for the regression based on difference equations, missing measurements were added using linear interpolation.
Only 25 days have missing measurements.
Based on the average dwell time approach and a set of Kronecker delta functions, a unified measurement model is established to represent the phenomena of missing measurements, time delays and nonlinearities.
The missing measurements are considered the finite-time framework.
The missing measurements appear in a random way which is governed by missing rates obeying a certain probability distribution.
Then, based on the minimum mean square error (MMSE) principle, a new linear optimal filter is designed such that, for the finite-step autocorrelated process noises, random one-step sensor delay and missing measurements, the estimation error is minimized.
Sensor saturations, missing measurements and channel fadings are governed by random variables obeying the Bernoulli distributions.
The systems under consideration are subjected to time delays, multiplicative noises and randomly occurring missing measurements.
The phenomena of ROQ and missing measurements are governed by a Bernoulli distributed stochastic sequence.
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