IEEE transactions on neural networks and learning systems
May 2, 2022
Neuromorphic systems are a viable alternative to conventional systems for real-time tasks with constrained resources. Their low power consumption, compact hardware realization, and low-latency response characteristics are the key ingredients of such ...
IEEE transactions on neural networks and learning systems
May 2, 2022
The biologically discovered intrinsic plasticity (IP) learning rule, which changes the intrinsic excitability of an individual neuron by adaptively turning the firing threshold, has been shown to be crucial for efficient information processing. Howev...
IEEE transactions on neural networks and learning systems
May 2, 2022
Neurophysiological observations confirm that the brain not only is able to detect the impaired synapses (in brain damage) but also it is relatively capable of repairing faulty synapses. It has been shown that retrograde signaling by astrocytes leads ...
Computational intelligence and neuroscience
Apr 28, 2022
XOR is a special nonlinear problem in artificial intelligence (AI) that resembles multiple real-world nonlinear data distributions. A multiplicative neuron model can solve these problems. However, the multiplicative model has the indigenous problem o...
Nature communications
Apr 26, 2022
Neuromorphic hardware that emulates biological computations is a key driver of progress in AI. For example, memristive technologies, including chalcogenide-based in-memory computing concepts, have been employed to dramatically accelerate and increase...
The journal of physical chemistry letters
Apr 22, 2022
Memristors are candidate devices for constructing artificial neurons, synapses, and computational networks for brainlike information processing and sensory-motor autonomous systems. However, the dynamics of natural neurons and synapses are challengin...
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...
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. ...
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...
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...