| 摘要 |
A neural network apparatus for processing input information, supplied as a data array, for a prespecified application to indicate output categories characteristics of the processing for that application. In the invention, an input stage accepts the data array and converts it to a corresponding internal representation, and a data preprocessor analyzes the data array based on a plurality of feature attribute measures. A neural network, comprising a plurality of interconnected neurons, processes the attribute measures to reach a neural state representative of corresponding category-attributes; portions of the network are predefined to include a number of neurons and prespecified with a particular correspondence to the feature attributes to accept corresponding attribute measures for the data array, and portions of the network are prespecified with a particular correspondence to the category attributes. A data postprocessor indicates the category attributes by correlating the neural state with predefined category attribute measures, and an output stage combines the category measures in a prespecified manner to generate an output category for the input information. Correspondingly, a method of training a neural network which has reached a predefined capacity for information storage so that more information may be imprinted on the network. |
