Decision making based on spike time dependent plasticity of a neural network
AssigneeThe Regents of the University of California
InventorsSteven Skorheim, Maksim Bazhenov, Pavel Sanda
Life of this patent
Estimating the term…
Loading patent…
AssigneeThe Regents of the University of California
InventorsSteven Skorheim, Maksim Bazhenov, Pavel Sanda
Estimating the term…
Systems, devices, and methods are disclosed for decision making based on plasticity rules of a neural network. A method may include obtaining a multilayered model. The multilayered model may include an input layer including one or more input units. The multilayered model may include one or more hidden layers including one or more hidden units. Each input unit may have a first connection with at least one hidden unit. The multilayered model may include an output layer including one or more output units. The method may also include receiving an input at a first input unit. The method may include sending a first signal from the first input unit to at least one hidden unit via a first connection comprising a first strength. The method may also include making a decision based on the model receiving the input.
A method for training a neural network model, the method comprising:
A system comprising:
Non-transitory computer-readable medium storing instructions, which when executed by one or more processing resources, cause the one or more processing resources to:
Dependencies are inferred from the claim text.