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Content Provider | IEEE Xplore Digital Library |
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Author | Fayomii, C.J.B. Sawan, M. Bennis, S. |
Copyright Year | 1995 |
Description | Author affiliation: Dept. of Electr. & Comput. Eng., Ecole Polytech. de Montreal, Que., Canada (Fayomii, C.J.B.; Sawan, M.) |
Abstract | A new approach for implementing a parallel VLSI architecture of a simplified Kalman filter (information filter) with unknown noise statistics is described. At the system level, the proposed approach is applied to a semi-systolic VLSI array to accelerate the matrix operations required in each iteration. In order to maximize the parallelism, a new architecture called the tri-trapezoidal array for implementing the Schur complement algorithm is proposed. The computations steps are decomposed into 2(m+1) parts executable in parallel. This decomposition decreases the computation time by 55%. The overall architecture exhibits a high performance and can be used for real time applications. |
Starting Page | 117 |
Ending Page | 119 |
File Size | 354946 |
Page Count | 3 |
File Format | |
ISBN | 0780327667 |
ISSN | 08407789 |
DOI | 10.1109/CCECE.1995.528088 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1995-09-05 |
Publisher Place | Canada |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Very large scale integration Information filters Computer architecture Information filtering Statistics Matrix decomposition Parallel processing Recursive estimation Kalman filters Covariance matrix |
Content Type | Text |
Resource Type | Article |
Subject | Electrical and Electronic Engineering Hardware and Architecture |
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