Fast Kalman filtering on quasilinear dendritic trees

Kalman filtering in pairwise Markov trees

An important problem in multiresolution analysis of signals or images consists in estimating hidden random variables x 1⁄4 fxsgs2S from observed ones y 1⁄4 fysgs2S. This is done classically in the context of hidden Markov trees (HMT). HMT have been extended recently to the more general context of pairwise Markov trees (PMT). In this note, we propose an adaptive filtering algorithm which is an e...

Kalman Filtering

Consider the following state space model (signal and observation model). Y t = H t X t + W t , W t ∼ N (0, R) (1) X t = F t X t−1 + U t , U t ∼ N (0, Q) (2)

Parallel Kalman Filtering on the Connection Machine

A parallel algorithm for square root Kalman filtering is developed and implemented on the Connection Machine (CM). The algorithm makes efficient use of parallel prefix or scan operations which are primitive instructions in the CM. Performance measurements show that the CM filter runs in time linear in the state vector size. This represents a great improvement over serial implementations which r...

Applying Kalman Filtering on a Quadruped Robot

Instrumentation design based on optimal Kalman filtering

This paper presents a methodology for locating sensors in dynamic systems. It aims to maximize Kalman filtering performance by using accuracy as its main performance index. To accomplish this task, both the measurement noise and the observation matrices are manipulated. The method has been applied in two academic case studies and in the Tennessee Eastman Challenge Problem and has shown promisin...