COMPUTING ASSOCIATION PROBABILITIES USING MEAN-FIELD APPROXIMATION NETWORKS

Wang Xiaofan; Song Wenzhong

Volume 19 Issue 1

Jan. 1997

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 1997 > 19(1): 24-30

Wang Xiaofan, Song Wenzhong . COMPUTING ASSOCIATION PROBABILITIES USING MEAN-FIELD APPROXIMATION NETWORKS[J]. Journal of Electronics & Information Technology, 1997, 19(1): 24-30.

Citation:

Wang Xiaofan, Song Wenzhong . COMPUTING ASSOCIATION PROBABILITIES USING MEAN-FIELD APPROXIMATION NETWORKS[J]. Journal of Electronics & Information Technology, 1997, 19(1): 24-30.

Wang Xiaofan, Song Wenzhong . COMPUTING ASSOCIATION PROBABILITIES USING MEAN-FIELD APPROXIMATION NETWORKS[J]. Journal of Electronics & Information Technology, 1997, 19(1): 24-30.

Citation:

Wang Xiaofan, Song Wenzhong . COMPUTING ASSOCIATION PROBABILITIES USING MEAN-FIELD APPROXIMATION NETWORKS[J]. Journal of Electronics & Information Technology, 1997, 19(1): 24-30.

PDF( 1077 KB)

COMPUTING ASSOCIATION PROBABILITIES USING MEAN-FIELD APPROXIMATION NETWORKS

Received Date: 1995-09-05
Rev Recd Date: 1995-10-11
Publish Date: 1997-01-19

Abstract

Abstract

The data assciation problem is one of the key problems of multitarget tracking in dense multiple return environments. By constructing a suitable energy function, the average values of a Boltzmann machine (T = 1) are approximately equal to the association probabilities. Then, a new method for computing association probabilities using mean-field approximation network is presented. The simulations show that this method is effective.

FullText(HTML)

References(1)

References

周宏仁,敬忠良,王培德.机动目标跟踪.北京:国防工业出版社,1991,第十三章.[2]Sengupta D, Iltis R. Neural solution to the multitarget tracking data association problem. IEEE Trans. on AES, 1989, AES-25(1): 96-108.[3]敬忠良等.基于随机神经网络的数据关联组合优化研究.控制理论与应用,1994,13(1): 257-263.[4]Zhou B, Bose N K. A comprehensive analysis of Neural solution to the multitarget tracking data association problem0. IEEE Trans. on AES, 1993, AES-29(1): 260-263.[5]Iltis R, Ting P-Y. Computing association probabilities using parallel Boltzmann machines. IEEE Trans. on NN, 1993, NN-4(2): 221-233.[6]Hinton, G. et al. Boltzmann machines: Constraint satisfaction networks that learn. 1984, CMU-SC-84-119.[7]Ackley D, et al. A learning algorithm for Boltzmann machines[J].Cognitive Sci.1985, 9(1):147-169[8]Kong S Y. Digital Neural Network. New York: Prentice Hall, 1993, Ch.9.[9]焦李成.神经网络计算.西安:西安电子科技大学出版社,1993, 107-110.

Relative Articles

Supplements(0)

Cited By

Proportional views