AIMC Topic: Neurons

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Multistability analysis of delayed recurrent neural networks with a class of piecewise nonlinear activation functions.

Neural networks : the official journal of the International Neural Network Society Apr 21, 2022
This paper studies the multistability of delayed recurrent neural networks (DRNNs) with a class of piecewise nonlinear activation functions. The coexistence as well as the stability of multiple equilibrium points (EPs) of DRNNs are proved. With the B...
Neurons Neural Networks, Computer Computer Simulation Algorithms Time Factors
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Artificial neural networks with conformable transfer function for improving the performance in thermal and environmental processes.

Neural networks : the official journal of the International Neural Network Society Apr 21, 2022
This research proposes a novel transfer function based on the hyperbolic tangent and the Khalil conformable exponential function. The non-integer order transfer function offers a suitable neural network configuration because of its ability to adapt. ...
Neurons Algorithms Neural Networks, Computer
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Parallel transmission in a synthetic nerve.

Nature chemistry Apr 21, 2022
Bioelectronic devices that are tetherless and soft are promising developments in medicine, robotics and chemical computing. Here, we describe bioinspired synthetic neurons, composed entirely of soft, flexible biomaterials, capable of rapid electroche...
Robotics Water Hydrogels Lipid Bilayers Neurons
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The neural coding framework for learning generative models.

Nature communications Apr 19, 2022
Neural generative models can be used to learn complex probability distributions from data, to sample from them, and to produce probability density estimates. We propose a computational framework for developing neural generative models inspired by the...
Brain Neurons Neural Networks, Computer Learning
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Memristor-based analogue computing for brain-inspired sound localization with in situ training.

Nature communications Apr 19, 2022
The human nervous system senses the physical world in an analogue but efficient way. As a crucial ability of the human brain, sound localization is a representative analogue computing task and often employed in virtual auditory systems. Different fro...
Learning Sound Localization Neurons Neural Networks, Computer Brain Humans
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Artificial Olfactory Neuron for an In-Sensor Neuromorphic Nose.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Apr 15, 2022
A neuromorphic module of an electronic nose (E-nose) is demonstrated by hybridizing a chemoresistive gas sensor made of a semiconductor metal oxide (SMO) and a single transistor neuron (1T-neuron) made of a metal-oxide-semiconductor field-effect tran...
Oxides Neurons Neural Networks, Computer Electronic Nose Smell
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A Layered Spiking Neural System for Classification Problems.

International journal of neural systems Apr 12, 2022
Biological brains have a natural capacity for resolving certain classification tasks. Studies on biologically plausible spiking neurons, architectures and mechanisms of artificial neural systems that closely match biological observations while giving...
Neural Networks, Computer Neurons Algorithms Brain Machine Learning
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A Photoelectric Spiking Neuron for Visual Depth Perception.

Advanced materials (Deerfield Beach, Fla.) Apr 11, 2022
The biological visual system encodes optical information into spikes and processes them by the neural network, which enables the perception with high throughput of visual processing with ultralow energy budget. This has inspired a wide spectrum of de...
Visual Perception Depth Perception Neural Networks, Computer Neurons
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A Neural Network-Based Model for Predicting Saybolt Color of Petroleum Products.

Sensors (Basel, Switzerland) Apr 6, 2022
Saybolt color is a standard measurement scale used to determine the quality of petroleum products and the appropriate refinement process. However, the current color measurement methods are mostly laboratory-based, thereby consuming much time and bein...
Linear Models Petroleum Neurons Algorithms Neural Networks, Computer
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A framework for preparing a stochastic nonlinear integrate-and-fire model for integrated information theory.

Network (Bristol, England) Apr 5, 2022
This paper presents a framework for spiking neural networks to be prepared for the Integrated Information Theory (IIT) analysis, using a stochastic nonlinear integrate-and-fire model. The model includes the crucial dynamics of the all-or-none law and...
Models, Neurological Information Theory Stochastic Processes Computer Simulation Neurons Reproducibility of Results Neural Networks, Computer Action Potentials
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