AIMC Topic: Neural Networks, Computer

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Noninvasive reconstruction of cardiac transmembrane potentials using a kernelized extreme learning method.

Physics in medicine and biology
Non-invasively reconstructing the cardiac transmembrane potentials (TMPs) from body surface potentials can act as a regression problem. The support vector regression (SVR) method is often used to solve the regression problem, however the computationa...

Identification of a small set of plasma signalling proteins using neural network for prediction of Alzheimer's disease.

Bioinformatics (Oxford, England)
MOTIVATION: Alzheimer's disease (AD) is a dementia that gets worse with time resulting in loss of memory and cognitive functions. The life expectancy of AD patients following diagnosis is ∼7 years. In 2006, researchers estimated that 0.40% of the wor...

Team activity recognition in Association Football using a Bag-of-Words-based method.

Human movement science
In this paper, a new methodology is used to perform team activity recognition and analysis in Association Football. It is based on pattern recognition and machine learning techniques. In particular, a strategy based on the Bag-of-Words (BoW) techniqu...

Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

PloS one
To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crosso...

Cognitive network neuroscience.

Journal of cognitive neuroscience
Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapi...

A spiking neural network based on the basal ganglia functional anatomy.

Neural networks : the official journal of the International Neural Network Society
We introduce a spiking neural network of the basal ganglia capable of learning stimulus-action associations. We model learning in the three major basal ganglia pathways, direct, indirect and hyperdirect, by spike time dependent learning and consideri...

Further analysis of global μ-stability of complex-valued neural networks with unbounded time-varying delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, we consider the problem of global μ-stability for complex-valued neural networks (CVNNs) with unbounded time-varying delays and it has been widely investigated. Under mild conditions, some new sufficient conditions for global μ-stabili...

Learning document semantic representation with hybrid deep belief network.

Computational intelligence and neuroscience
High-level abstraction, for example, semantic representation, is vital for document classification and retrieval. However, how to learn document semantic representation is still a topic open for discussion in information retrieval and natural languag...

Epidemics in interconnected small-world networks.

PloS one
Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-wor...

The application of data mining techniques to oral cancer prognosis.

Journal of medical systems
This study adopted an integrated procedure that combines the clustering and classification features of data mining technology to determine the differences between the symptoms shown in past cases where patients died from or survived oral cancer. Two ...