Temporal spike encoding for temporal learning
AssigneeQUALCOMM Incorporated
InventorsDavid Jonathan JULIAN, Venkata Sreekanth Reddy ANNAPUREDDY, Kristopher David PETERSON
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Abstract
Certain aspects of the present disclosure support methods and apparatus for temporal spike encoding for temporal learning in an artificial nervous system. The temporal spike encoding for temporal learning can comprise obtaining sensor data being input into the artificial nervous system, processing the sensor data to generate feature vectors, converting element values of the feature vectors into delays, and causing at least one artificial neuron of the artificial nervous system to spike at times based on the delays.
Claims34
A method for operating an artificial nervous system, comprising:
- obtaining sensor data being input into the artificial nervous system;
- processing the sensor data to generate feature vectors;
- converting element values of the feature vectors into delays;
- and
- causing at least one artificial neuron of the artificial nervous system to spike at times based on the delays.
An apparatus for operating an artificial nervous system, comprising:
- a sensor configured to obtain sensor data being input into the artificial nervous system;
- a first circuit configured to process the sensor data to generate feature vectors;
- a second circuit configured to convert element values of the feature vectors into delays;
- and
- a third circuit configured to cause at least one artificial neuron of the artificial nervous system to spike at times based on the delays.
An apparatus for operating an artificial nervous system, comprising:
- means for obtaining sensor data being input into the artificial nervous system;
- means for processing the sensor data to generate feature vectors;
- means for converting element values of the feature vectors into delays;
- and
- means for causing at least one artificial neuron of the artificial nervous system to spike at times based on the delays.
A computer-readable medium having instructions executable by a computer stored thereon for:
- obtaining sensor data being input into an artificial nervous system;
- processing the sensor data to generate feature vectors;
- converting element values of the feature vectors into delays;
- and
- causing at least one artificial neuron of the artificial nervous system to spike at times based on the delays.
Dependencies are inferred from the claim text.