An overview of biomimetic robots with animal behaviors
Z Gao, Q Shi, T Fukuda, C Li, Q Huang - Neurocomputing, 2019 - Elsevier
The study of biomimetic robots and that of animal behaviors are mutually-reinforcing and
inseparable. Animals, through long-term evolutionary processes, have developed innate …
inseparable. Animals, through long-term evolutionary processes, have developed innate …
A review of algorithms and hardware implementations for spiking neural networks
Deep Learning (DL) has contributed to the success of many applications in recent years.
The applications range from simple ones such as recognizing tiny images or simple speech …
The applications range from simple ones such as recognizing tiny images or simple speech …
Periodic and chaotic spiking behaviors in a simplified memristive Hodgkin-Huxley circuit
Abstract The famous Hodgkin-Huxley circuit contains two time-varying resistors to describe
the electrophysiological characteristics of sodium and potassium ion channels. But the time …
the electrophysiological characteristics of sodium and potassium ion channels. But the time …
Nadol: Neuromorphic architecture for spike-driven online learning by dendrites
Biologically plausible learning with neuronal dendrites is a promising perspective to improve
the spike-driven learning capability by introducing dendritic processing as an additional …
the spike-driven learning capability by introducing dendritic processing as an additional …
A low-cost high-speed neuromorphic hardware based on spiking neural network
Neuromorphic is a relatively new interdisciplinary research topic, which employs various
fields of science and technology, such as electronic, computer, and biology. Neuromorphic …
fields of science and technology, such as electronic, computer, and biology. Neuromorphic …
Digital hardware implementation of Morris-Lecar, Izhikevich, and Hodgkin-Huxley neuron models with high accuracy and low resources
The neuron can be called the main cell of a nervous system that can transmit messages from
one neuron to another neuron or another cell through electrical signals. In neuromorphic …
one neuron to another neuron or another cell through electrical signals. In neuromorphic …
The implementation and optimization of neuromorphic hardware for supporting spiking neural networks with MLP and CNN topologies
W Ye, Y Chen, Y Liu - … on Computer-Aided Design of Integrated …, 2022 - ieeexplore.ieee.org
Spiking neural network (SNN) has attracted extensive attention in large-scale image
processing tasks. To obtain higher computing efficiency, the development of hardware …
processing tasks. To obtain higher computing efficiency, the development of hardware …
Efficient Digital Realization of Endocrine Pancreatic -Cells
The accurate implementation of biological neural networks, which is one of the important
areas of research in the field of neuromorphic, can be studied in the case of diseases …
areas of research in the field of neuromorphic, can be studied in the case of diseases …
High speed and low digital resources implementation of Hodgkin-Huxley neuronal model using base-2 functions
Neurons are the basic blocks in the Central Nervous System (CNS). Simulation and
hardware realization of these blocks are vital in neuromorphic engineering. This paper …
hardware realization of these blocks are vital in neuromorphic engineering. This paper …
A digital implementation of neuron–astrocyte interaction for neuromorphic applications
Recent neurophysiologic findings have shown that astrocytes play important roles in
information processing and modulation of neuronal activity. Motivated by these findings, in …
information processing and modulation of neuronal activity. Motivated by these findings, in …