Influence of the Unit Number of Intermediate Layers and Networks on Learning Ability | Zendy

Hideto Ide | Zendy; Hiroyuki Endo | Zendy; Sizuaki Takahashi | Zendy

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Influence of the Unit Number of Intermediate Layers and Networks on Learning Ability

Author(s) -

Hideto Ide,

Hiroyuki Endo,

Sizuaki Takahashi

Publication year - 1990

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.1990.p0118

Subject(s) - unit (ring theory) , computer science , vocabulary learning , artificial neural network , artificial intelligence , vocabulary , mathematics , mathematics education , philosophy , linguistics

Learning ability of networks in the recognition of vocabulary, etc. using neural networks is notably influenced by the unit number of intermediate layers. In our current study, we have investigated the effects when the unit number of intermediate layers is changed during the course of learning when back-propagation is applied, thereby discussing eventual influence on the learning ability of networks.

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