Patent ID: 10496922

Abstract:
Described is a system for adapting neural networks. The system receives inputs to be learned by a multi-layered spiking neural network. A first mechanism is implemented to adapt weights on the connections via competition among neurons using Hebbian learning. Activity levels of the neurons are stabilized to allow the multi-layered spiking neural network to learn the inputs. A second mechanism is implemented to increase a learning rate of a neuron over time using Hebbian learning. A third mechanism is implemented, wherein newly created neurons, representing new inputs, copy at least one synaptic structure of older neurons in the multi-layered spiking neural network. The mechanisms are used for continuous, online learning of the inputs to the multi-layered spiking neural network. An autonomous system, such as an autonomous vehicle, can use the learned inputs to learn from its environment and perform tasks, such as classification and prediction.