Sentence examples for innovation sequences from inspiring English sources

Owing to high nonlinearity of chemical process dynamics, it is likely that innovation sequences are non-Gaussian.

A simple robust Kalman filtering (RKF) scheme with weighted matrices of innovation sequences is introduced for local state estimation.

Bracketing close to 95% of the innovation sequences within two standard deviations from the mean, the filter is found to be well behaved.

The innovation sequences of EKFs are monitored by several statistical tests to detect the presence of a failure and to localize the failures in all AD sensors.

where the covariance of residual innovation sequence is.

Diagnostics of the electromechanic actuator is done by means of the properties of the innovation sequence of the designed filter.

Based on the obtained theoretical results, an approach to detect failures that affect the mean and variance of the innovation sequence have been considered.

The signal quality index, together with the KF innovation sequence, is also used to weight multiple independent estimates of the respiratory rate from independent KFs.

Exploration of the behaviour of some innovation based parameters useful in adaptive filter and system integrity designs, including covariance of innovation sequence, degree of mismatch (DOM), and degree of divergence (DOD), etc., is also involved.

Adaptive Kalman filtering (AKF) scheme modifies the noise covariance matrix (Q and R) value based on a window of past innovation sequence whereas SKF is a window based filtering technique which uses past information to obtain the present state estimate.

The Extended Kalman Filter (EKF) is developed for nonlinear flight dynamic estimation of an F-16 fighter and the effects of the sensor and control surface/actuator failures in the innovation sequence of the designed EKF are investigated.