Functional model of biological neural networks [PDF]
Cognitive Neurodynamics, 2010 A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate ...
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Cellular computation and cognition
Frontiers in Computational Neuroscience, 2023 Contemporary neural network models often overlook a central biological fact about neural processing: that single neurons are themselves complex, semi-autonomous computing systems.
W. Tecumseh Fitch
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Exploiting Device Mismatch in Neuromorphic VLSI Systems to Implement Axonal Delays [PDF]
, 2012 Sheik S, Chicca E, Indiveri G. Exploiting Device Mismatch in Neuromorphic VLSI Systems to Implement Axonal Delays. Presented at the International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia.Axonal delays are used in neural ...
Chicca, Elisabetta +2 more
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Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network [PDF]
Journal of Physical Chemistry A, 2020 Chemical reactions occur in energy, environmental, biological, and many other natural systems, and the inference of the reaction networks is essential to understand and design the chemical processes in engineering and life sciences.
Weiqi Ji, Sili Deng
semanticscholar +1 more source
A Novel Evaluation Strategy to Artificial Neural Network Model Based on Bionics
Journal of Bionic Engineering, 2021 With the continuous deepening of Artificial Neural Network (ANN) research, ANN model structure and function are improving towards diversification and intelligence. However, the model is more evaluated from the pros and cons of the problem-solving results
Sen Tian +5 more
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Predefined-time synchronization of inertial memristive neural networks
Nantong Daxue xuebao. Ziran kexue ban, 2023 Based on a novel control protocol, the synchronization problem of predefined-time of neural networks with inertia and memristor is studied. The network model considered in this paper can be widely used to simulate biological synapses, and has good ...
JIANG Zhuyan; LIU Xiaoyang
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CHOOSING THE MODEL OF BIOLOGICAL NEURAL NETWORK FOR IMAGE SEGMENTATION OF A BIO-LIQUID FACIE
Vestnik KRAUNC: Fiziko-Matematičeskie Nauki, 2019 In the paper, the biological neural network models are analyzed with a purpose to solve the problems of segmentation and pattern recognition when applied to the bio-liquid facies obtained by the cuneiform dehydration method.
M. E. Semenov, T.Yu. Zablotskaya
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Unsupervised Spiking Neural Network with Dynamic Learning of Inhibitory Neurons
Sensors, 2023 A spiking neural network (SNN) is a type of artificial neural network that operates based on discrete spikes to process timing information, similar to the manner in which the human brain processes real-world problems.
Geunbo Yang +7 more
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Stability of a neural network model with small-world connections
, 2004 Small-world networks are highly clustered networks with small distances among the nodes. There are many biological neural networks that present this kind of connections.
C. Aguirre +15 more
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Neural Sampling by Irregular Gating Inhibition of Spiking Neurons and Attractor Networks [PDF]
, 2016 A long tradition in theoretical neuroscience casts sensory processing in the brain as the process of inferring the maximally consistent interpretations of imperfect sensory input.
Indiveri, Giacomo, Muller, Lorenz K.
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