Parallel implementation of reinforcement learning Q-learning technique for FPGA
Q-learning is an off-policy reinforcement learning technique, which has the main advantage
of obtaining an optimal policy interacting with an unknown model environment. This paper …
of obtaining an optimal policy interacting with an unknown model environment. This paper …
Embedded multimodal interfaces in robotics: applications, future trends, and societal implications
In the past, robots were primarily used to perform work that was either too hard, too
dangerous or simply too repetitive for humans, eg, assembly line work, or work that could be …
dangerous or simply too repetitive for humans, eg, assembly line work, or work that could be …
[HTML][HTML] A hybrid FPGA-based system for EEG-and EMG-based online movement prediction
A current trend in the development of assistive devices for rehabilitation, for example
exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality …
exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality …
Network-on-Chip based MPSoC architecture for k-mean clustering algorithm
Data and image segmentation plays pivotal role in the application of machine learning. k-
means, as a tool for unsupervised clustering, is a widely used algorithm for segmentation …
means, as a tool for unsupervised clustering, is a widely used algorithm for segmentation …
Proposta de arquitetura em hardware para fpga da técnica qlearning de aprendizagem por reforço
LMD Silva - 2016 - repositorio.ufrn.br
O Q-learning é uma técnica de aprendizagem por reforço off-policy que tem como principal
vantagem a possibilidade de obter uma política ótima interagindo com o ambiente sem que …
vantagem a possibilidade de obter uma política ótima interagindo com o ambiente sem que …
Highly scalable processor architecture for reinforcement learning
S Pawanekar, G Udgirkar - 2020 Third International …, 2020 - ieeexplore.ieee.org
Q-Learning is also referred as a reinforcement learning method. Its main advantage is that of
obtaining a near optimal policy while interfacing with an unknown model. This paper …
obtaining a near optimal policy while interfacing with an unknown model. This paper …
A Novel Architecture for k-means Clustering Algorithm
Technological advancements in todays information age has helped the researchers to
capture digital footprints of humans with regards to their daily activities. These logs of …
capture digital footprints of humans with regards to their daily activities. These logs of …
14Embedded Multimodal Interfaces in Robotics: Applications, Future
In the past, robots were primarily used to perform work that was either too hard, too
dangerous or simply too repetitive for humans, eg, assembly line work, or work that could be …
dangerous or simply too repetitive for humans, eg, assembly line work, or work that could be …
A Novel Architecture for k-means Clustering Algorithm
SA Khan - Proceedings of the Third International Afro-European …, 2017 - books.google.com
Technological advancements in todays information age has helped the researchers to
capture digital footprints of humans with regards to their daily activities. These logs of …
capture digital footprints of humans with regards to their daily activities. These logs of …
[引用][C] TH-SOF-1375-Network-on-Chip based Application Speci c Processors for Frequent Pattern Mining Algorithms
SG Khawaja - 2018 - NUST, College of electrical and …