The MDP policy linearizes probabilistic QoS constraints and provably achieves near-optimal utility and stability in multi-infrastructure-sharing networks, with error vanishing in the frame size.
Learning by mistakes in memristor networks
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
Recent results in adaptive matter revived the interest in the implementation of novel devices able to perform brain-like operations. Here we introduce a training algorithm for a memristor network which is inspired in previous work on biological learning. Robust results are obtained from computer simulations of a network of voltage controlled memristive devices. Its implementation in hardware is straightforward, being scalable and requiring very little peripheral computation overhead.
citation-role summary
background 1
citation-polarity summary
fields
cs.NI 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
A QoS Framework for Service Provision in Multi-Infrastructure-Sharing Networks
The MDP policy linearizes probabilistic QoS constraints and provably achieves near-optimal utility and stability in multi-infrastructure-sharing networks, with error vanishing in the frame size.