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pro vyhledávání: '"Smith, James E."'
Autor:
Smith, James E.
The macrocolumn is a key component of a neuromorphic computing system that interacts with an external environment under control of an agent. Environments are learned and stored in the macrocolumn as labeled directed graphs where edges connect feature
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2e753631969407c0352c7717a68bc02
Autor:
Smith, James E.
This document is focused on computing systems implemented in technologies that communicate and compute with temporal transients. Although described in general terms, implementations of spiking neural networks are of primary interest. As background, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13bea26a5827ea9aef65953a56c1b65a
Autor:
Smith, James E.
A Temporal Neural Network (TNN) architecture for implementing efficient online reinforcement learning is proposed and studied via simulation. The proposed T-learning system is composed of a frontend TNN that implements online unsupervised clustering
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ce32c98b8969464c02f01c231c9bea0
Autor:
Smith, James E.
A long-standing proposition is that by emulating the operation of the brain's neocortex, a spiking neural network (SNN) can achieve similar desirable features: flexible learning, speed, and efficiency. Temporal neural networks (TNNs) are SNNs that co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e6ae18309d9b6b4cc4b3eb856eb371f7
Autor:
Smith, James E.
A computational paradigm based on neuroscientific concepts is proposed and shown to be capable of online unsupervised clustering. Because it is an online method, it is readily amenable to streaming realtime applications and is capable of dynamically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f1e20fce569f9c60886c88d4eb96168