Method and apparatus for processing data in a neural network
First Claim
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1. An apparatus for processing data in a neural network having a stored sample transfer function, comprising:
- a receiver configured to receive at least one input value representing information to be processed by the network;
a threshold processor configured to determine threshold values indicating boundaries for application of the sample transfer function for a node, the threshold processor comprising;
a mapper configured to receive a value representing a specific transfer function for the node and map the received value to identify threshold values for the specific transfer function;
a generator configured to generate an intermediate value from the input value for the node; and
an output processor configured to determine an output value for the node based on the threshold values and the intermediate value in accordance with the sample transfer function.
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Abstract
A digital artificial neural network (ANN) reduces memory requirements by storing sample transfer function representing output values for multiple nodes. Each nodes receives an input value representing the information to be processed by the network. Additionally, the node determines threshold values indicative of boundaries for application of the sample transfer function for the node. From the input value received, the node generates an intermediate value. Based on the threshold values and the intermediate value, the node determines an output value in accordance with the sample transfer function.
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Citations
7 Claims
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1. An apparatus for processing data in a neural network having a stored sample transfer function, comprising:
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a receiver configured to receive at least one input value representing information to be processed by the network; a threshold processor configured to determine threshold values indicating boundaries for application of the sample transfer function for a node, the threshold processor comprising; a mapper configured to receive a value representing a specific transfer function for the node and map the received value to identify threshold values for the specific transfer function; a generator configured to generate an intermediate value from the input value for the node; and an output processor configured to determine an output value for the node based on the threshold values and the intermediate value in accordance with the sample transfer function. - View Dependent Claims (2, 3, 4)
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5. A computer program product comprising:
a computer usable medium having computer readable code embodied therein for processing data in a neural network, the computer usable medium comprising; a receiving module configured to receive an input value representing information to be processed by the network; a threshold processing module configured to determine threshold values indicating boundaries for application of a sample transfer function for a node, said threshold processing module comprising; a defining module configured to define a value representing a specific transfer function for the node; and a mapping module configured to map the defined value to identify threshold values for the specific transfer function; a determining module configured to determine an intermediate value from the input value for the node; and an output processing module configured to determine an output value for the node based on the threshold values and the intermediate value in accordance with the sample transfer function. - View Dependent Claims (6, 7)
Specification