Adaptive learning system and method
First Claim
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1. A neural network program embodied on a computer-readable medium comprising:
- an input layer comprising one or more input nodes arranged to receive input data;
a rule base layer comprising one or more rule nodes;
an output layer comprising one or more output nodes, each rule node in the rule base layer having a minimum activation threshold and each rule node arranged to be activated when input data satisfies the minimum activation threshold of the rule node; and
an adaptive component arranged to aggregate selected two or more rule nodes in the rule base layer based on the input data.
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Abstract
A neural network module including an input layer having one or more input nodes arranged to receive input data, a rule base layer having one or more rule nodes, an output layer having one or more output nodes, and an adaptive component arranged to aggregate selected two or more rule nodes in the rule base layer based on the input data, an adaptive learning system having one or more of the neural network modules, related methods of implementing the neural network module and an adaptive learning system, and a neural network program.
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Citations
36 Claims
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1. A neural network program embodied on a computer-readable medium comprising:
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an input layer comprising one or more input nodes arranged to receive input data; a rule base layer comprising one or more rule nodes; an output layer comprising one or more output nodes, each rule node in the rule base layer having a minimum activation threshold and each rule node arranged to be activated when input data satisfies the minimum activation threshold of the rule node; and an adaptive component arranged to aggregate selected two or more rule nodes in the rule base layer based on the input data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. An adaptive learning program embodied on a computer readable medium comprising more than one neural network program each neural network program comprising:
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an input layer comprising one or more input nodes arranged to receive input data; a rule base layer comprising one or more rule nodes, each rule node in the rule base layer having a minimum activation threshold and each rule node arranged to be activated when input data satisfies the minimum activation threshold of the rule node; an output layer comprising one or more output nodes; and an adaptive component arranged to aggregate selected two or more rule nodes in the rule base layer based on the input data.
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14. A neural network module comprising:
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an input layer comprising one or more input nodes arranged to receive input data; a rule base layer comprising one or more rule nodes, each rule node having a minimum activation threshold, each rule node configured to be activated where when input data satisfies the minimum activation threshold of the rule node; an output layer comprising one or more output nodes; and an adaptation component arranged to aggregate selected two or more rule nodes in the rule base layer based on the input data, and to increase the minimum activation threshold of one or more rule nodes not selected for aggregation. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. An adaptive learning system comprising more than one neural network module, each neural network module comprising:
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an input layer comprising one ore more input nodes arranged to receive input data; a rule base layer comprising one or more rule nodes, each rule node having a minimum activation threshold and each rule node configured to be activated when input data satisfies the minimum activation threshold of the rule node; an output layer comprising one or more output nodes; and an adaptation component arranged to aggregate selected two or more rule nodes in the rule base layer based on the input data, and to increase the minimum activation threshold of one or more rule nodes not selected for aggregation.
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26. A method of implementing a neural network module comprising the steps of:
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maintaining in computer memory an input layer comprising one or more input nodes to receive input data; maintaining in computer memory a rule base layer comprising one or more rule nodes; assigning a minimum activation threshold to each rule node in the rule base layer, each rule node being activated when input data satisfies the minimum activation threshold of the rule node; maintaining in computer memory an output layer comprising one or more output nodes; aggregating selected two or more rule nodes in the rule base layer based on the input data; and increasing the minimum activation threshold of one or more rule nodes not selected for aggregation. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
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Specification