In an era where autonomous systems demand pinpoint accuracy, navigation algorithms face a tough trade-off between precision and speed.

Vold and Leuridan [1] introduced in 1993 an algorithm for high resolution, slew rate independent order tracking based on the concepts of Kalman filters [5, 6]. The algorithm has been highly successful ...

M. Bierlaire, F. Crittin, An Efficient Algorithm for Real-Time Estimation and Prediction of Dynamic OD Tables, Operations Research, Vol. 52, No. 1 (Jan. - Feb., 2004 ...

This example estimates the normal SSM of the mink-muskrat data using the EM algorithm. The mink-muskrat series are detrended. Refer to Harvey (1989) for details of this data set. Since this EM ...

This course introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. It develops the background theoretical topics in state ...

The automated driving developer community typically uses Eigen*, a C++ math library, for the matrix operations required by the Extended Kalman Filter algorithm. EKF usually involves many small ...

The Stanford-developed ReFIT (or Recalibrated Feedback Intention-Trained Kalman filter) algorithm harnesses this with a silicon chip which is implanted into the brain of the subject and records ...