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2000

On the Internal Representations of Product Units

8 years 10 months ago
On the Internal Representations of Product Units
This paper explores internal representation power of product units [1] that act as the functional nodes in the hidden layer of a multi-layer feedforward network. Interesting properties from using binary input provide an insight into the superior computational power of the product unit. Using binary computation problems of symmetry and parity as illustrative examples, we show that learning arbitrary complex internal representations is more achievable with product units than with traditional summing units. Key words: product unit, internal representations, recurrent neural networks, perceptrons, backpropagation training.
Jung-Hua Wang, Yi-Wei Yu, Jia-Horng Tsai
Added 19 Dec 2010
Updated 19 Dec 2010
Type Journal
Year 2000
Where NPL
Authors Jung-Hua Wang, Yi-Wei Yu, Jia-Horng Tsai
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