7 citations · 16 across the 9 of their papers we have counts for
9 papers
Neuromorphic Online Clustering and Its Application to Spike Sorting
James E. Smith
Active dendrites are the basis for biologically plausible neural networks possessing many desirable features of the biological brain including flexibility, dynamic adaptability, an…
Implementing Online Reinforcement Learning with Clustering Neural Networks
James E. Smith
An agent employing reinforcement learning takes inputs (state variables) from an environment and performs actions that affect the environment in order to achieve some objective. Re…
A Macrocolumn Architecture Implemented with Spiking Neurons
James E. Smith
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…
Implementing Online Reinforcement Learning with Temporal Neural Networks
James E. Smith
A Temporal Neural Network (TNN) architecture for implementing efficient online reinforcement learning is proposed and studied via simulation. The proposed T-learning system is comp…
Temporal Computer Organization
James E. Smith
This document is focused on computing systems implemented in technologies that communicate and compute with temporal transients. Although described in general terms, implementation…
A Microarchitecture Implementation Framework for Online Learning with Temporal Neural Networks
Harideep Nair, John Paul Shen, James E. Smith
Temporal Neural Networks (TNNs) are spiking neural networks that use time as a resource to represent and process information, similar to the mammalian neocortex. In contrast to com…