Apparatus and methods for state-dependent learning in spiking neuron networks
Number of patents in Portfolio can not be more than 2000
United States of America Patent
Stats
-
Mar 24, 2015
Grant Date -
N/A
app pub date -
Dec 20, 2012
filing date -
Dec 20, 2012
priority date (Note) -
In Force
status (Latency Note)
Importance
Abstract
State-dependent supervised learning framework in artificial neuron networks may be implemented. A framework may be used to describe plasticity updates of neuron connections based on a connection state term and a neuron state term. Connection states may be updated based on inputs and outputs to and/or from neurons. The input connections of a neuron may be updated using input traces comprising a time-history of inputs provided via the connection. Weight of the connection may be updated and connection state may be time varying. The updated weights may be determined using a rate of change of the input trace and a term comprising a product of a per-neuron contribution and a per-connection contribution configured to account for the state time-dependency. Using event-dependent connection change components, connection updates may be executed on a per neuron basis, as opposed to a per-connection basis.
First Claim
Family
International Classification(s)
Cited Art Landscape
Patent Citation Ranking
Advertisement
Advertisement
Advertisement
Recipient Email Address
Recipient Email Address
Comment
Recipient Email Address
Add to Portfolio(s)
To add this patent to one, or more, of your portfolios, simply click the add button.
This Patent is in these Portfolios:
Add to additional portfolios:
Last Refreshed On:
Changes done successfully