ArticleFrontiers in neurorobotics2022
R-STDP Spiking Neural Network Architecture for Motion Control on a Changing Friction Joint Robotic Arm.
Article in Frontiers in neurorobotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Backpropagation-free spiking neural networks with the forward-forward algorithm.Scientific reports · 2026Article
- Reinforced liquid state machines-new training strategies for spiking neural networks based on reinforcements.Frontiers in computational neuroscience · 2025Article
- Overview of Spiking Neural Network Learning Approaches and Their Computational Complexities.Sensors (Basel, Switzerland) · 2023Review
- Implementation of Kalman Filtering with Spiking Neural Networks.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
4 authors.
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Abstract
Neuromorphic computing is a recent class of brain-inspired high-performance computer platforms and algorithms involving biologically-inspired models adopting hardware implementation in integrated circuits. The neuromorphic computing applications have provoked the rise of highly connected neurons and synapses in analog circuit systems that can be used to solve today's challenging machine learning problems. In conjunction with biologically plausible learning rules, such as the Hebbian learning and memristive devices, biologically-inspired spiking neural networks are considered the next-generation neuromorphic hardware construction blocks that will enable the deployment of new analog
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Registered trials
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