Affiliation: | Department of Automation Tsinghua University, Beijing, 100084, China Department of Industrial and Manufacturing Systems Engineering Kansas State University, Manhattan, KS 66506, U.S.A. |
Abstract: | Mathematical essence and structures of the feedforward neural networks are investigated in this paper. The interpolation mechanisms of the feedforward neural networks are explored. For example, the well-known result, namely, that a neural network is an universal approximator, can be concluded naturally from the interpolative representations. Finally, the learning algorithms of the feedforward neural networks are discussed. |