DocumentCode
288869
Title
An adaptive neural PDA approach based on an united Hopfield-BP network
Author
Tao, Tao
Author_Institution
Beijing Univ. of Aeronaut. & Astronaut., China
Volume
6
fYear
1994
fDate
27 Jun- 2 Jul 1994
Firstpage
3967
Abstract
An adaptive neural probabilistic data association (A.NPDA) approach, which is a modification of the NPDA approach proposed previously, is put forward in this paper. All the features of the joint PDA (JPDA) are included in a united Hopfield neural network. The A.NPDA has an important feature of adaptive adjustment to the variation of return density and target number. The simulation results prove the parallel algorithm is a simplified but perfect imitation of the JPDA
Keywords
Hopfield neural nets; probability; adaptive neural probabilistic data association; backpropagation; joint probabilistic data association; return density; target number; united Hopfield neural network; Concurrent computing; Constraint optimization; Hopfield neural networks; Information filtering; Information filters; Neurons; Parallel algorithms; Personal digital assistants; Target tracking; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374846
Filename
374846
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