A survey of robotics control based on learning-inspired spiking neural networks
Biological intelligence processes information using impulses or spikes, which makes those
living creatures able to perceive and act in the real world exceptionally well and outperform …
living creatures able to perceive and act in the real world exceptionally well and outperform …
Toward reflective spiking neural networks exploiting memristive devices
The design of modern convolutional artificial neural networks (ANNs) composed of formal
neurons copies the architecture of the visual cortex. Signals proceed through a hierarchy …
neurons copies the architecture of the visual cortex. Signals proceed through a hierarchy …
Spatial properties of STDP in a self-learning spiking neural network enable controlling a mobile robot
SA Lobov, AN Mikhaylov, M Shamshin… - Frontiers in …, 2020 - frontiersin.org
Development of spiking neural networks (SNNs) controlling mobile robots is one of the
modern challenges in computational neuroscience and artificial intelligence. Such networks …
modern challenges in computational neuroscience and artificial intelligence. Such networks …
CARLsim 6: an open source library for large-scale, biologically detailed spiking neural network simulation
Mature simulation systems for Spiking Neural Networks (SNNs) become more relevant than
ever for understanding the brain and supporting neuromorphic computing. The CARL-sim …
ever for understanding the brain and supporting neuromorphic computing. The CARL-sim …
Adaptive robot path planning using a spiking neuron algorithm with axonal delays
A path planning algorithm for outdoor robots, which is based on neuronal spike timing, is
introduced. The algorithm is inspired by recent experimental evidence for experience …
introduced. The algorithm is inspired by recent experimental evidence for experience …
Spatial memory in a spiking neural network with robot embodiment
Cognitive maps and spatial memory are fundamental paradigms of brain functioning. Here,
we present a spiking neural network (SNN) capable of generating an internal representation …
we present a spiking neural network (SNN) capable of generating an internal representation …
Biomimetic tactile sensors and signal processing with spike trains: A review
The sense of touch plays a critical role in enabling human beings to interact with the
surrounding environments. As robots move from laboratories to domestic environments, they …
surrounding environments. As robots move from laboratories to domestic environments, they …
Dynamic reliability management in neuromorphic computing
Neuromorphic computing systems execute machine learning tasks designed with spiking
neural networks. These systems are embracing non-volatile memory to implement high …
neural networks. These systems are embracing non-volatile memory to implement high …
Skin-inspired flexible and stretchable electrospun carbon nanofiber sensors for neuromorphic sensing
During the past few decades, a significant amount of research effort has been dedicated
toward developing skin-inspired sensors for real-time human motion monitoring and next …
toward developing skin-inspired sensors for real-time human motion monitoring and next …
[PDF][PDF] Pattern classification by spiking neural networks combining self-organized and reward-related spike-timing-dependent plasticity
S Nobukawa, H Nishimura, T Yamanishi - Journal of Artificial …, 2019 - sciendo.com
Many recent studies have applied to spike neural networks with spike-timing-dependent
plasticity (STDP) to machine learning problems. The learning abilities of …
plasticity (STDP) to machine learning problems. The learning abilities of …