Comparative computational analysis of a new per-sample partitioning linear filter and the Kalman filter-Reference-Cited by-同舟云学术

Comparative computational analysis of a new per-sample partitioning linear filter and the Kalman filter

Published:1987-01 Issue:2 Volume:18 Page:351-370
ISSN:0020-7721
Container-title:International Journal of Systems Science
language:en
Short-container-title:International Journal of Systems Science

Author:

ANAGNOSTOU K. E.,LAINIOTIS D. G.

Publisher

Informa UK Limited

Subject

Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering

Link

http://www.tandfonline.com/doi/pdf/10.1080/00207728708963972

Reference7 articles.

1. ANDRISANI , D. , 1978 , Multipartitioned estimation algorithms . Ph.D. thesis , State University of New York at Buffalo .

2. COSMIDIS , E. T. , 1980 , Analysis of algorithms for discrete stochastic estimation . Ph.D. thesis . State University of New York at Buffalo ; 1983, Proc. ofMelecon ’83 (Athens I.E.E.E. Press), 2, C4.06 .

3. On computational efficiency of linear filtering algorithms

4. A New Approach to Linear Filtering and Prediction Problems

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A new class of efficient adaptive nonlinear filters (ANLF);IEEE Transactions on Signal Processing;1998-06

2. A New Computationally Effective Algorithm for Solving the Discrete Riccati Equation;Journal of Mathematical Analysis and Applications;1994-09

3. New doubling algorithm for the discrete periodic Riccati Equation;Applied Mathematics and Computation;1994-02

4. On the parallel implementations of the linear Kalman and Lainiotis filters and their efficiency;Signal Processing;1991-12

5. Optimal seismic deconvolution;Signal Processing;1988-12