Numerous algorithms have been proposed to allow legged robots to learn to walk. However, most of these algorithms are devised to learn walking in a straight line, which is not sufficient to accomplish any real-world mission. Here we introduce the Tra...
Inspired by the fact that the division of labor and cooperation play extremely important roles in the human history development, this paper develops a novel artificial bee colony algorithm based on information learning (ILABC, for short). In ILABC, a...
Neural networks : the official journal of the International Neural Network Society
Jan 10, 2015
Constructing an informative and discriminative graph plays an important role in various pattern recognition tasks such as clustering and classification. Among the existing graph-based learning models, low-rank representation (LRR) is a very competiti...
Imitation and learning from humans require an adequate sensorimotor controller to learn and encode behaviors. We present the Dynamic Muscle Perception-Action(DM-PerAc) model to control a multiple degrees-of-freedom (DOF) robot arm. In the original Pe...
IEEE transactions on bio-medical engineering
Jan 9, 2015
The current diagnosis process of dementia is resulting in a high percentage of cases with delayed detection. To address this problem, in this paper, we explore the feasibility of autonomously detecting mild cognitive impairment (MCI) in the older adu...
Journal of applied clinical medical physics
Jan 8, 2015
The accuracy of the CyberKnife Synchrony Respiratory Tracking System (SRTS) is considered to be patient-dependent because the SRTS relies on an individual correlation between the internal tumor position (ITP) and the external marker position (EMP), a...
IEEE journal of biomedical and health informatics
Jan 6, 2015
The study reported herein proposes a new method for the diagnosis of epilepsy from electroencephalography (EEG) signals based on complex classifiers. To carry out this study, first the features of EEG data are extracted using a dual-tree complex wave...
IEEE transactions on neural networks and learning systems
Jan 6, 2015
In this paper, the problem of energy-to-peak state estimation for a class of discrete-time Markov jump recurrent neural networks (RNNs) with randomly occurring nonlinearities (RONs) and time-varying delays is investigated. A practical phenomenon of n...
MOTIVATION: Glycosylation is a ubiquitous type of protein post-translational modification (PTM) in eukaryotic cells, which plays vital roles in various biological processes (BPs) such as cellular communication, ligand recognition and subcellular reco...
Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for...
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