| 摘要 |
Polynomial processors learn expert system rules, for either business or real-time applications, to improve the robustness and speed of execution of the expert system. One or more polynomial processors are constructed which incorporate the production rules of one or more expert systems. Each polynomial processor is constructed of computing elements or neuron circuits each having only one significant processing element in the form of a multiplier. Each polynomial processor utilizes a training algorithm which does not require repetitive training and which yields a global minimum to each given set of input vectors.
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