Complex network methodology is very useful for complex system explorer. However, the relationships among variables in complex system are usually not clear. Therefore, inferring association networks among variables from their observed data has been a ...
IEEE/ACM transactions on computational biology and bioinformatics
Nov 1, 2016
MicroRNAs (miRNAs) are known as an important indicator of cancers. The presence of cancer can be detected by identifying the responsible miRNAs. A fuzzy-rough entropy measure (FREM) is developed which can rank the miRNAs and thereby identify the rele...
International journal of neural systems
Sep 9, 2016
This paper presents a state-of-the-art application of fractional hopfield neural networks (FHNNs) to defend against chip cloning attacks, and provides insight into the reason that the proposed method is superior to physically unclonable functions (PU...
Computational intelligence and neuroscience
Sep 8, 2016
This paper presents a novel fault diagnosis method for analog circuits using ensemble empirical mode decomposition (EEMD), relative entropy, and extreme learning machine (ELM). First, nominal and faulty response waveforms of a circuit are measured, r...
Neural networks : the official journal of the International Neural Network Society
Aug 24, 2016
The goal of reinforcement learning is to learn an optimal policy which controls an agent to acquire the maximum cumulative reward. The model-based reinforcement learning approach learns a transition model of the environment from data, and then derive...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 23, 2016
We present a novel method to segment retinal images using ensemble learning based convolutional neural network (CNN) architectures. An entropy sampling technique is used to select informative points thus reducing computational complexity while perfor...
Neural networks : the official journal of the International Neural Network Society
Jul 18, 2016
We define in this work a new localized version of a Vapnik-Chervonenkis (VC) complexity, namely the Local VC-Entropy, and, building on this new complexity, we derive a new generalization bound for binary classifiers. The Local VC-Entropy-based bound ...
Computer methods and programs in biomedicine
Jun 1, 2016
BACKGROUND AND OBJECTIVES: Extraction of blood vessels on retinal images plays a significant role for screening of different opthalmologic diseases. However, accurate extraction of the entire and individual type of vessel silhouette from the noisy im...
IEEE transactions on pattern analysis and machine intelligence
Feb 23, 2016
We propose minimum entropy rate simplification (MERS), an information-theoretic, parameterization-independent framework for simplifying generative models of stochastic processes. Applications include improving model quality for sampling tasks by conc...
Loss of postural center-of-pressure complexity (COP complexity) has been associated with reduced adaptability that accompanies disease and aging. The aim of this study was to identify if COP complexity is reduced: (1) in those with Multiple Sclerosis...