Anzeige
Erschienen in:
2012 | OriginalPaper | Buchkapitel
Silicon Neurons That Compute
verfasst von : Swadesh Choudhary, Steven Sloan, Sam Fok, Alexander Neckar, Eric Trautmann, Peiran Gao, Terry Stewart, Chris Eliasmith, Kwabena Boahen
Erschienen in: Artificial Neural Networks and Machine Learning – ICANN 2012
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
We use neuromorphic chips to perform arbitrary mathematical computations for the first time. Static and dynamic computations are realized with heterogeneous spiking silicon neurons by programming their weighted connections. Using 4K neurons with 16M feed-forward or recurrent synaptic connections, formed by 256K local arbors, we communicate a scalar stimulus, quadratically transform its value, and compute its time integral. Our approach provides a promising alternative for extremely power-constrained embedded controllers, such as fully implantable neuroprosthetic decoders.