Yoshifusa Ito

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We have constructed one-hidden-layer neural networks capable of approximating polynomials and their derivatives simultaneously. Generally, optimizing neural network parameters to be trained at later steps of the BP training is more difficult than optimizing those to be trained at the first step. Taking into account this fact, we suppressed the number of(More)
Any number of linearly independent plane waves can be obtained by scaling, shifting and/or rotating a plane wave created from an activation function. We investigate the condition which ensures linear independence of the plane waves. In the case all the three procedures are combined, the linear independence can be proved by ad hoe methods for most of(More)