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Volume 21 Issue 2
Mar.  1999
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Haifeng SANG, Zizhen CHEN. 3D Human Motion Prediction Based on Bi-directionalGated Recurrent Unit[J]. Journal of Electronics & Information Technology, 2019, 41(9): 2256-2263. doi: 10.11999/JEIT180978
Citation: Li Shouli, Li Jinyan, Li Wangchao. SPARSED CONNECTION WEIGHTS OF HIGHER-ORDER NEURAL NETWORK AND ITS PRUNING ALGORITHM[J]. Journal of Electronics & Information Technology, 1999, 21(2): 182-185.

SPARSED CONNECTION WEIGHTS OF HIGHER-ORDER NEURAL NETWORK AND ITS PRUNING ALGORITHM

  • Received Date: 1997-08-25
  • Rev Recd Date: 1998-07-26
  • Publish Date: 1999-03-19
  • In this paper, the fully-connected higher-order neuron and sparsed higher-order neuron are introduced, the mapping capabilities of the fully-connected higher-order neural networks are investigated, and that arbitrary Boolean function defined from {0,1}N can be realized by fully-connected higher-order neural networks is proved. Based on this, in order to simplify the networks architecture, a pruning algorithm for eliminating the redundant connection weights is also proposed, which can be applied to the implementation of sparsed higher-order neural classifier. The simulated results show the effectiveness of the algorithm.
  • Paretto P, Niez J J. Long term memory storage capacity of multiconnected neural networks, Biol[J].Cybern.1986, 54(3):53-63[2]Baldi P. Neural networks, orientations of the supercube and algebraic threshold functions, IEEE Trans. on Inform. Theory, 1988, IT-34 (3): 523-530.[3]Giles C L, Maxwell T. Learning, invariance, and generalization in high-order neural networks, Applied Optics, 1987, 26(23): 4972-4978.[4]Giles C L, Chen D, Miller C B, et al. Second-order recurrent neural networks for grammatical[5]inference, Proc. Int. Joint Conf. Neural Networks, IJCNN91, Seattle: vo1.2, 1991, 273-281.Lion R, Azimi-Sadjadi M R, Dent R. Detection of dim targets in high cluttered background using high order correlation neural network, Proc. Int. Conf. Neural Networks, IJCNN91, Seattle: vol.1, 1991, 701-706.[6]Shun-ichi Amari. Dualistic geometry of the manifold of higher-order neurons, Neural Networks, 1991, 4(5): 443-451.[7]李金艳.稀疏高阶神经网络的通近能力及其算法的研究:[博士论文].华南理工大学,1996.[8]李金艳,余英林.二层高阶神经网络对任意布尔函数的实现,华南理工大学学报,1995, 23(10): 111-116.[9]Fahner G, Eckmiller R. Structural adaption of parsimonious higher-order neural classifiers, Neural Networks, 1994, 7(2): 279-289.
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