AIMC Topic: Neural Networks, Computer

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A linear functional strategy for regularized ranking.

Neural networks : the official journal of the International Neural Network Society
Regularization schemes are frequently used for performing ranking tasks. This topic has been intensively studied in recent years. However, to be effective a regularization scheme should be equipped with a suitable strategy for choosing a regularizati...

Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.

Neural computation
Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we ...

Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design.

ISA transactions
This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to de...

Characterizing air quality data from complex network perspective.

Environmental science and pollution research international
Air quality depends mainly on changes in emission of pollutants and their precursors. Understanding its characteristics is the key to predicting and controlling air quality. In this study, complex networks were built to analyze topological characteri...

A Fast SVD-Hidden-nodes based Extreme Learning Machine for Large-Scale Data Analytics.

Neural networks : the official journal of the International Neural Network Society
Big dimensional data is a growing trend that is emerging in many real world contexts, extending from web mining, gene expression analysis, protein-protein interaction to high-frequency financial data. Nowadays, there is a growing consensus that the i...

Constructing general partial differential equations using polynomial and neural networks.

Neural networks : the official journal of the International Neural Network Society
Sum fraction terms can approximate multi-variable functions on the basis of discrete observations, replacing a partial differential equation definition with polynomial elementary data relation descriptions. Artificial neural networks commonly transfo...

Noise-enhanced convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generali...

Finite-time synchronization of fractional-order memristor-based neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, we consider the problem of finite-time synchronization of a class of fractional-order memristor-based neural networks (FMNNs) with time delays and investigated it potentially. By using Laplace transform, the generalized Gronwall's ineq...

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications.

Neural networks : the official journal of the International Neural Network Society
The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to de...