Increased dynamic range artificial neuron network apparatus and methods
First Claim
1. An electronic device having computerized logic, the computerized logic configured to be placed in operation with a network node of a network in order to:
- evaluate a value of an input into the network node;
when the evaluation indicates that the input value is above a threshold, generate a scaled input using a concave function of the input; and
when the evaluation indicates that the input value is not above the threshold, generate a bypass input;
wherein the scaled input is characterized by a magnitude that is lower than a magnitude of the input value.
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Abstract
Apparatus and methods for processing inputs by one or more neurons of a network. The neuron(s) may generate spikes based on receipt of multiple inputs. Latency of spike generation may be determined based on an input magnitude. Inputs may be scaled using for example a non-linear concave transform. Scaling may increase neuron sensitivity to lower magnitude inputs, thereby improving latency encoding of small amplitude inputs. The transformation function may be configured compatible with existing non-scaling neuron processes and used as a plug-in to existing neuron models. Use of input scaling may allow for an improved network operation and reduce task simulation time.
251 Citations
20 Claims
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1. An electronic device having computerized logic, the computerized logic configured to be placed in operation with a network node of a network in order to:
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evaluate a value of an input into the network node; when the evaluation indicates that the input value is above a threshold, generate a scaled input using a concave function of the input; and when the evaluation indicates that the input value is not above the threshold, generate a bypass input; wherein the scaled input is characterized by a magnitude that is lower than a magnitude of the input value. - View Dependent Claims (2, 3)
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4. A computer readable apparatus having a non-transitory storage medium with at least one computer program stored thereon, the at least one computer program configured to, when executed:
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generate a transformed input of a plurality of spiking inputs of a neuron of a spiking neuron network; and communicate the transformed input to the neuron; wherein; the generation of the transformed input is configured to cause the neuron to encode an input within an expanded range into a latency of a spike output, the expanded range characterized by greater span of input values compared to an input range of the neuron in an absence of a transformation. - View Dependent Claims (5, 6, 7, 8)
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9. A method of adapting an extant logical network to provide a desired functionality, the method comprising:
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placing a logical entity in communication with a node; where the logical entity is configured to process a plurality of inputs for the node of the extant logical network; receiving one or more inputs of the plurality of inputs; and causing the extant logical network to operate in accordance with the desired functionality based at least on a transformation of the one or more inputs by the logical entity; wherein the rule is effectuated based at least on an evaluation of a value of individual ones of the one or more inputs by the logical entity; and wherein the logical entity is configured such that; when the evaluation indicates that the value is within a range, the transformation produces an output equal to the value; and when the evaluation indicates that the value is outside the range, the transformation produces an output different from the value. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification