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| An Improved Method of Kalman Filter Based on Neural Network |
| Jiang Ens-ong; Li Meng-chao; Sun Liu-jie |
| Optical & Electronic Information Enginering College, University of Shanghai for Science and Technology, Shanghai 200093, China |
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Abstract Kalman filter is a recursive filtering method based on minimum variance estimation, but it assumes that the signal’s state model is exactly known, which restricts its application in practice. Nevertheless the system’s state equation can be obtained through the identification of systems by using neural network’s good abilities of non-linear mapping. In contrast to some classic improved algorithm of Kalman filtering, this method has the advantages of wide application range, simple and feasible mathematical modeling. In this paper, the method which integrates neural network and Kalman filter is implemented for image restoration. The experiment result shows that the provided method is effective and available.
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Received: 23 February 2006
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2007, Vol. 29 
