Journal ArticleDOI
Neural networks
Alberto Prieto,Beatriz Prieto,Eva M. Ortigosa,Eduardo Ros,Francisco J. Pelayo,Julio Ortega,Ignacio Rojas +6 more
TLDR
The development and evolution of different topics related to neural networks is described showing that the field has acquired maturity and consolidation, proven by its competitiveness in solving real-world problems.About:
This article is published in Neurocomputing.The article was published on 2016-11-19. It has received 184 citations till now. The article focuses on the topics: Neural modeling fields & Nervous system network models.read more
Citations
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Journal ArticleDOI
Comparison of EEG signal decomposition methods in classification of motor-imagery BCI
Eltaf Abdalsalam Mohamed,Mohd Zuki Yusoff,Aamir Saeed Malik,Mohammad Rida Bahloul,Dalia Mahmoud Adam,Ibrahim Khalil Adam +5 more
TL;DR: This work demonstrates that binary and four-class movements of the left and right feet and hands can be classified using recorded EEG signals of the motor cortex, and an intrinsic time-scale decomposition (ITD) feature extraction method can be used for real time brain computer interface.
Book ChapterDOI
Novel Methodology for Cardiac Arrhythmias Classification Based on Long-Duration ECG Signal Fragments Analysis
Paweł Pławiak,Moloud Abdar +1 more
TL;DR: This chapter investigates a cardiac disorders database (ECG) with 17 classes (normal sinus rhythm, the rhythm of the pacemaker, and fifteen arrhythmias) using a novel classification methodology using a new evolutionary-neural system, based on the SVM classifier.
Journal ArticleDOI
Double-Level Locally Weighted Extreme Learning Machine for Soft Sensor Modeling of Complex Nonlinear Industrial Processes
TL;DR: A Double-level Locally Weighted Extreme Learning Machine (DLWELM) based soft sensor modeling method, which has higher prediction precision compared to the basic ELM methods.
Journal Article
Enhanced Hybrid Global MPPT Algorithm for PV Systems operating under Fast-Changing Partial Shading Conditions
TL;DR: A global maximum power point tracking algorithm including an artificial neural network and a hill climbing method is combined, which is suitably designed for handling fast changing partial shading conditions in photovoltaic systems.
Journal ArticleDOI
A neural network approach for retailer risk assessment in the aftermarket industry
TL;DR: In this paper, a model for risk assessment with a hexagonal grid and 2D self-organizing map was applied, which can provide a basis for classification of retailers based on specified risk levels defined by the experts and risk managers of the company.
References
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Fuzzy sets
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Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
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The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
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Reinforcement Learning: An Introduction
TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Statistical learning theory
TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.