Characteristics of Small Scale Non-Monotonic Neuron Networks Having Large Potentiality for Learning

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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4

Como, Italy

July 24-July 27

ISBN: 0-7695-0619-4

	ASCII Text	x
	Mitsunaga Kinjo, Shigeo Sato, Koji Nakajima, "Characteristics of Small Scale Non-Monotonic Neuron Networks Having Large Potentiality for Learning," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 4, pp. 4171, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4, 2000.

	BibTex	x
	@article{ 10.1109/IJCNN.2000.860768, author = {Mitsunaga Kinjo and Shigeo Sato and Koji Nakajima}, title = {Characteristics of Small Scale Non-Monotonic Neuron Networks Having Large Potentiality for Learning}, journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on}, volume = {4}, year = {2000}, issn = {1098-7576}, pages = {4171}, doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.860768}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on TI - Characteristics of Small Scale Non-Monotonic Neuron Networks Having Large Potentiality for Learning SN - 1098-7576 SP EP A1 - Mitsunaga Kinjo, A1 - Shigeo Sato, A1 - Koji Nakajima, PY - 2000 VL - 4 JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on ER -

Mitsunaga Kinjo, Tohoku University

Shigeo Sato, Tohoku University

Koji Nakajima, Tohoku University

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.860768

In this paper, we report a study on learning ability of a Deterministic Boltzmann Machine (DBM) [1, 2] with neurons, which have a non-monotonic activation function. We use an end-cut-off-type function with a threshold parameter '?' as the non-monotonic function. Numerical simulations of nonlinear problems, such as the 2-Parity problem and the 4-Parity problem, show that the DBM network with non-monotonic neurons has higher learning ability compared to the network with monotonic neurons.

Citation:

Mitsunaga Kinjo, Shigeo Sato, Koji Nakajima, "Characteristics of Small Scale Non-Monotonic Neuron Networks Having Large Potentiality for Learning," ijcnn, vol. 4, pp.4171, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4, 2000

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