Retrotransposons can cause somatic genome variation in the human nervous system, which is hypothesized to have relevance to brain development and neuropsychiatric disease. However, the detection of individual somatic mobile element insertions present...
IEEE transactions on neural networks and learning systems
Jan 4, 2021
Deep neural networks (DNNs), characterized by sophisticated architectures capable of learning a hierarchy of feature representations, have achieved remarkable successes in various applications. Learning DNN's parameters is a crucial but challenging t...
Neural networks : the official journal of the International Neural Network Society
Jan 2, 2021
We analyse mathematically the constraints on weights resulting from Hebbian and STDP learning rules applied to a spiking neuron with weight normalisation. In the case of pure Hebbian learning, we find that the normalised weights equal the promotion p...
With the continuous improvement of automation and informatization, the electromagnetic environment has become increasingly complex. Traditional protection methods for electronic systems are facing with serious challenges. Biological nervous system ha...
Neural networks : the official journal of the International Neural Network Society
Dec 29, 2020
A typical feature of hyperbox-based dendrite morphological neurons (DMN) is the generation of sharp and rough decision boundaries that inaccurately track the distribution shape of classes of patterns. This feature is because the minimum and maximum a...
Neural networks : the official journal of the International Neural Network Society
Dec 28, 2020
Efficient and robust motion perception systems are important pre-requisites for achieving visually guided flights in future micro air vehicles. As a source of inspiration, the visual neural networks of flying insects such as honeybee and Drosophila p...
Neural networks : the official journal of the International Neural Network Society
Dec 23, 2020
Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs. It has become the go-to methodology for tackling image restoration and has outperfo...
International journal of neural systems
Dec 22, 2020
In contrast to the previous artificial neural networks (ANNs), spiking neural networks (SNNs) work based on temporal coding approaches. In the proposed SNN, the number of neurons, neuron models, encoding method, and learning algorithm design are desc...
Critical reviews in food science and nutrition
Dec 17, 2020
Artificial neural network (ANN) is a simplified model of the biological nervous system consisting of nerve cells or neurons. The application of ANN to food process engineering is relatively novel. ANN had been employed in diverse applications like fo...
BACKGROUND: Ca-imaging is a powerful tool to measure neuronal dynamics and network activity. To monitor network-level changes in cultured neurons, neuronal activity is often evoked by electrical or optogenetic stimulation and assessed using multi-ele...