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Found 9 papers, 0 papers with code
Implementing Online Reinforcement Learning with Clustering Neural Networks
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.
A Macrocolumn Architecture Implemented with Spiking Neurons
The macrocolumn is a key component of a neuromorphic computing system that interacts with an external environment under control of an agent.
Implementing Online Reinforcement Learning with Temporal Neural Networks
A Temporal Neural Network (TNN) architecture for implementing efficient online reinforcement learning is proposed and studied via simulation.
Temporal Computer Organization
This restriction is removed by allowing use of the synchronizing clock as an additional function input that acts as a temporal reference value.
A Microarchitecture Implementation Framework for Online Learning with Temporal Neural Networks
Temporal Neural Networks (TNNs) are spiking neural networks that use time as a resource to represent and process information, similar to the mammalian neocortex.
A Temporal Neural Network Architecture for Online Learning
A TNN architecture is proposed, and, as a proof-of-concept, TNN operation is demonstrated within the larger context of online supervised classification.
Direct CMOS Implementation of Neuromorphic Temporal Neural Networks for Sensory Processing
The TNN microarchitecture framework is embodied in a set of characteristic equations for assessing the total gate count, die area, compute time, and power consumption for any TNN design.
A Neuromorphic Paradigm for Online Unsupervised Clustering
The paradigm is implemented as a cognitive column that incorporates five key elements: 1) temporal coding, 2) an excitatory neuron model for inference, 3) winner-take-all inhibition, 4) a column architecture that combines excitation and inhibition, 5) localized training via spike timing de-pendent plasticity (STDP).
(Newtonian) Space-Time Algebra
The space-time (s-t) algebra provides a mathematical model for communication and computation using values encoded as events in discretized linear (Newtonian) time.
