Functional-Link Net Computing: Theory, System Architecture, and Functionalities

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INPUT+ONE HIDDEN LAYER+OUTPUT 已經可以實現任意布爾函數。其實也可以是任意逼近 measurable函數。

MLP是universal approximators。既然One hidden layer的擬合能力已經這麼強,可以讓網路更寬一些。

Numerous and significant advantages accrue from using a flat net, including rapid quadratic optimization in the learning of weights, simplification in hardware as well as in computational procedures, and uniform system architecture for all four functionalities.

 

Functional-Link Net Computing: Theory, System Architecture, and Functionalities

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