Skip to main navigation
Skip to search
Skip to main content
TU Delft Research Portal Home
Help & FAQ
Link opens in a new tab
Search content at TU Delft Research Portal
Home
Research units
Researchers
Research output
Datasets
Projects
Equipment
Press/Media
Prizes
Activities
Spiking Neural-Networks-Based Data-Driven Control
Y. Liu, W. Pan
Robust Robot Systems
Research output
:
Contribution to journal
›
Article
›
Scientific
›
peer-review
233
Downloads (Pure)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Spiking Neural-Networks-Based Data-Driven Control'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
INIS
control
100%
neural networks
100%
learning
100%
data
100%
plasticity
55%
machine learning
22%
increasing
11%
dynamics
11%
convergence
11%
energy efficiency
11%
optimal control
11%
apparatus
11%
environment
11%
engineering
11%
Computer Science
Neural Network
100%
Control
100%
Learning Scheme
62%
Machine Learning
25%
Reinforcement Learning
25%
Energy Efficiency
12%
Model
12%
Control Decision
12%
temporal difference
12%
Can Controller
12%
Hardware
12%
Slow Convergence
12%
Network Controller
12%
Engineering
Learning Scheme
100%
Mechanisms
40%
Reinforcement Learning
40%
Environment
20%
Models
20%
Control Loop
20%
Characteristics
20%
High Energy Efficiency
20%
Neural Network Controller
20%
Optimal Control
20%
Learning Rule
20%
Control Engineering
20%
Neuroscience
Neural Network
100%
Spike-Timing-Dependent Plasticity
62%
Reinforcement Learning
25%
Chemical Engineering
Neural Network
100%
Learning System
25%
Reinforcement Learning
25%
Psychology
Neural Network
100%
Reinforcement
25%
Training
12%
Keyphrases
Spike-timing-dependent Plasticity Learning
71%
Pole Balancing
14%
Delayed Reward
14%