Neural networks : the official journal of the International Neural Network Society
Feb 2, 2016
This paper is concerned with the state estimation problem for a class of artificial neural networks (ANNs) without the assumptions of monotonicity or differentiability of the activation functions. The measured outputs are corrupted by stochastic nois...
Parkinson's disease (PD) is a movement disorder that affects the patient's nervous system and health-care applications mostly uses wearable sensors to collect these data. Since these sensors generate time stamped data, analyzing gait disturbances in ...
In multisource, "cocktail party" sound environments, human and animal auditory systems can use spatial cues to effectively separate and follow one source of sound over competing sources. While mechanisms to extract spatial cues such as interaural tim...
One of the most common diseases that affect human red blood cells (RBCs) is anaemia. To diagnose anaemia, the following methods are typically employed: an identification process that is based on measuring the level of haemoglobin and the classificati...
The increasing cost of drug development together with a significant drop in the number of new drug approvals raises the need for innovative approaches for target identification and efficacy prediction. Here, we take advantage of our increasing unders...
Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system...
Computational and mathematical methods in medicine
Jan 31, 2016
Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a lar...
Neural networks : the official journal of the International Neural Network Society
Jan 29, 2016
In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines is proposed by developing an ensemble of dynamic neural network identifiers. For health monitoring of the gas turbine engine, its dynamics is first identifie...
Despite the recent introduction of mass detection techniques, ultraviolet detection is still widely applied in the field of the chromatographic analysis of natural medicines. Here, a neural network cascade model consisting of nine small artificial ne...
Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with ...
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