[HTML][HTML] A survey of encoding techniques for signal processing in spiking neural networks
Biologically inspired spiking neural networks are increasingly popular in the field of artificial
intelligence due to their ability to solve complex problems while being power efficient. They …
intelligence due to their ability to solve complex problems while being power efficient. They …
Spiking neural networks and online learning: An overview and perspectives
Applications that generate huge amounts of data in the form of fast streams are becoming
increasingly prevalent, being therefore necessary to learn in an online manner. These …
increasingly prevalent, being therefore necessary to learn in an online manner. These …
Optimizing deeper spiking neural networks for dynamic vision sensing
Abstract Spiking Neural Networks (SNNs) have recently emerged as a new generation of
low-power deep neural networks due to sparse, asynchronous, and binary event-driven …
low-power deep neural networks due to sparse, asynchronous, and binary event-driven …
Memristor‐Based Intelligent Human‐Like Neural Computing
S Wang, L Song, W Chen, G Wang… - Advanced Electronic …, 2023 - Wiley Online Library
Humanoid robots, intelligent machines resembling the human body in shape and functions,
cannot only replace humans to complete services and dangerous tasks but also deepen the …
cannot only replace humans to complete services and dangerous tasks but also deepen the …
Unleashing the power of disruptive and emerging technologies amid COVID-19: A detailed review
The unprecedented outbreak of the novel coronavirus (COVID-19), during early December
2019 in Wuhan, China, has quickly evolved into a global pandemic, became a matter of …
2019 in Wuhan, China, has quickly evolved into a global pandemic, became a matter of …
[HTML][HTML] Brain-inspired learning in artificial neural networks: a review
Artificial neural networks (ANNs) have emerged as an essential tool in machine learning,
achieving remarkable success across diverse domains, including image and speech …
achieving remarkable success across diverse domains, including image and speech …
ECG classification algorithm based on STDP and R-STDP neural networks for real-time monitoring on ultra low-power personal wearable devices
A Amirshahi, M Hashemi - IEEE transactions on biomedical …, 2019 - ieeexplore.ieee.org
This paper presents a novel ECG classification algorithm for inclusion as part of real-time
cardiac monitoring systems in ultra low-power wearable devices. The proposed solution is …
cardiac monitoring systems in ultra low-power wearable devices. The proposed solution is …
[HTML][HTML] Visual explanations from spiking neural networks using inter-spike intervals
By emulating biological features in brain, Spiking Neural Networks (SNNs) offer an energy-
efficient alternative to conventional deep learning. To make SNNs ubiquitous, a 'visual …
efficient alternative to conventional deep learning. To make SNNs ubiquitous, a 'visual …
Spiking neural network on neuromorphic hardware for energy-efficient unidimensional slam
G Tang, A Shah, KP Michmizos - 2019 IEEE/RSJ International …, 2019 - ieeexplore.ieee.org
Energy-efficient simultaneous localization and mapping (SLAM) is crucial for mobile robots
exploring unknown environments. The mammalian brain solves SLAM via a network of …
exploring unknown environments. The mammalian brain solves SLAM via a network of …
Numerical spiking neural P systems
Spiking neural P (SN P) systems are a class of discrete neuron-inspired computation
models, where information is encoded by the numbers of spikes in neurons and the timing of …
models, where information is encoded by the numbers of spikes in neurons and the timing of …