2018
DOI: 10.1002/cae.21972
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Modeling, simulation, and implementation issues of CPGs for neuromorphic engineering applications

Abstract: Neuromorphic engineering is a discipline used to develop hardware, which can mimic the characteristics and abilities of biological systems by investigating their physiological structures and data transfer mechanisms. The recent studies about the neuromorphic systems mostly consist of robotic applications whose designs are inspired by Central Pattern Generators (CPGs). CPGs are special neural networks which can produce coordinated rhythmic activity patterns and these rhythmic movements are modeled mathematicall… Show more

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Cited by 14 publications
(2 citation statements)
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“…Also at the undergraduate level, but in the area of specialization of neuromorphic engineering applications, Korkmaz et al , presented a simulation‐centric 3‐week training course. The course integrates advanced topics in the areas of biophysical neuron models, oscillator models, and neural networks as forms of Central Pattern Generator (CPG) models, combining them with hardware structures to create robotics applications.…”
Section: Modeling‐and‐simulation‐centric Course Designmentioning
confidence: 99%
“…Also at the undergraduate level, but in the area of specialization of neuromorphic engineering applications, Korkmaz et al , presented a simulation‐centric 3‐week training course. The course integrates advanced topics in the areas of biophysical neuron models, oscillator models, and neural networks as forms of Central Pattern Generator (CPG) models, combining them with hardware structures to create robotics applications.…”
Section: Modeling‐and‐simulation‐centric Course Designmentioning
confidence: 99%
“…Neuromorphic engineering is a re-emerging field that seeks the development of brain-inspired devices based on computations performed through biological synapses [185]. The principles sustaining the foundation of biological nervous systems have been the inspiration for the development of neuromorphic based software and devices since the late 1980s.…”
Section: Gallium Lanthanum Sulfide Waveguides As a Cognitive Photonicmentioning
confidence: 99%