Nonlinear Dimensionality Reduction by Multi Layer Perceptron Using Superposed Energy
نویسندگان
چکیده
| We investigate an energy function for MLP called superposed energy. Applying to autoassociative learning of a sandglass-type MLP, it can adaptively adjust the e ective number of the bottlenecklayer units to the intrinsic dimensionality of nonlinear data, and the optimal dimensionality reduced representation can be extracted after learning.
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تاریخ انتشار 1999