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- W184935406 abstract "In this paper, we observe a new approach to learn non-linearly separable problems using a single multi-valued neuron. It is shown that a k-valued problem, which is non-linearly separable in the n-dimensional space can be projected into an m-valued (where m = kl) linearly separable problem in the same space. This projection can be utilized through a periodic activation function for the multi-valued neuron. Then the initial problem can be learned by a single multi-valued neuron using its learning algorithm. This approach is illustrated by the examples of such problems as XOR, Parity n, mod k addition of n variables and some benchmarks using a single multi-valued neuron." @default.
- W184935406 created "2016-06-24" @default.
- W184935406 creator A5052101553 @default.
- W184935406 date "2011-01-01" @default.
- W184935406 modified "2023-09-26" @default.
- W184935406 title "On the Projection of k-Valued Non-linearly Separable Problems into m-Valued Linearly Separable Problems" @default.
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- W184935406 doi "https://doi.org/10.1007/978-3-642-20206-3_15" @default.
- W184935406 hasPublicationYear "2011" @default.
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