Neural networks : the official journal of the International Neural Network Society
Mar 18, 2017
The visual cortex is both extensive and intricate. Computational models are needed to clarify the relationships between its local mechanisms and high-level functions. The Stabilized Supralinear Network (SSN) model was recently shown to account for ma...
Neural networks : the official journal of the International Neural Network Society
Mar 18, 2017
In an attempt to improve the forecasting accuracy of stock price fluctuations, a new one-step-ahead model is developed in this paper which combines empirical mode decomposition (EMD) with stochastic time strength neural network (STNN). The EMD is a p...
Identifying topics of discussions in online health communities (OHC) is critical to various information extraction applications, but can be difficult because topics of OHC content are usually heterogeneous and domain-dependent. In this paper, we prov...
Educational software (apps) can improve science education by providing an interactive way of learning about complicated topics that are hard to explain with text and static illustrations. However, few educational apps are available for simulation of ...
International journal of neural systems
Mar 16, 2017
In this research, a novel family of learning rules called Beta Hebbian Learning (BHL) is thoroughly investigated to extract information from high-dimensional datasets by projecting the data onto low-dimensional (typically two dimensional) subspaces, ...
Neural networks : the official journal of the International Neural Network Society
Mar 16, 2017
The present paper aims to propose a simple method to realize mutual information maximization for better interpretation and generalization. To train neural networks and obtain better performance, neurons should impartially consider as many input patte...
Neural networks : the official journal of the International Neural Network Society
Mar 16, 2017
We have studied neuronal synchronisation in a random network of adaptive exponential integrate-and-fire neurons. We study how spiking or bursting synchronous behaviour appears as a function of the coupling strength and the probability of connections,...
Proceedings of the National Academy of Sciences of the United States of America
Mar 14, 2017
The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature ...
PURPOSE: To construct, train, and apply an artificial neural network (ANN) system for prediction of different outcome variables of percutaneous nephrolithotomy (PCNL). We calculated predictive accuracy, sensitivity, and precision for each outcome var...
Proceedings of the National Academy of Sciences of the United States of America
Mar 13, 2017
Social behavior is often shaped by the rich storehouse of biographical information that we hold for other people. In our daily life, we rapidly and flexibly retrieve a host of biographical details about individuals in our social network, which often ...
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