IEEE transactions on neural networks and learning systems
Jul 17, 2014
In this paper, an optimized multilayer feed-forward network (MLFN) is developed to construct a soft sensor for controlling naphtha dry point. To overcome the two main flaws in the structure and weight of MLFNs, which are trained by a back-propagation...
IEEE transactions on neural networks and learning systems
Jul 15, 2014
In this paper, a two-layer recurrent neural network is proposed to solve the nonsmooth convex optimization problem subject to convex inequality and linear equality constraints. Compared with existing neural network models, the proposed neural network...
IEEE transactions on neural networks and learning systems
Jul 10, 2014
This paper proposes a learning from demonstration system based on a motion feature, called phase transfer sequence. The system aims to synthesize the knowledge on humanoid whole body motions learned during teacher-supported interactions, and apply th...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 5, 2014
Magnetic resonance imaging (MRI), particularly dynamic contrast enhanced (DCE) imaging, has shown great potential in prostate cancer diagnosis and staging. In the current practice of DCE-MRI, diagnosis is based on quantitative parameters extracted fr...
To achieve an excellent dual-arm coordination of the humanoid robot, it is essential to deal with the nonlinearities existing in the system dynamics. The literatures so far on the humanoid robot control have a common assumption that the problem of ou...
Neural networks : the official journal of the International Neural Network Society
Jun 9, 2014
Although it is very important to scrutinize recurrent structures of neural networks for elucidating brain functions, conventional methods often have difficulty in characterizing global loops within a network systematically. Here we applied the Hodge-...
We describe a novel hyper-heuristic system that continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics and samples problems from its environment; and representative problems and h...
Although previous bio-inspired models have concentrated on invertebrates (such as ants), mammals such as primates with higher cognitive function are valuable for modeling the increasingly complex problems in engineering. Understanding primates' socia...
PURPOSE: Long scanning time greatly hinders the widespread application of spin-lattice relaxation in rotating frame (T1ρ) in clinics. In this study, a novel method is proposed to reconstruct the T1ρ-weighted images from undersampled k-space data and ...
A number of domains in biomedical research use data with a large number of predictors all representing the same type of measurement. Often, an important summary is the within-person distribution of these predictors. Here we focus on settings where th...
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