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
Diagnostic performance of an artificial neural network to predict excess body fat in children.
Ibrahim Duran,Kyriakos Martakis,Kyriakos Martakis,Mirko Rehberg,Oliver Semler,Eckhard Schoenau +5 more
TL;DR: Waist circumference and z scores of body mass index are commonly used to predict childhood obesity, although BMI and WC have a limited sensitivity.
Proceedings ArticleDOI
The Use of Deep Learning in Speech Enhancement.
TL;DR: The model of DNN is used with two layers and has been compared with the ADALINE model to prove its efficacy.
Journal ArticleDOI
Ethical Reflections of Human Brain Research and Smart Information Systems
TL;DR: Ethical concerns with the use of SIS in human brain research include privacy and confidentiality, the security of personal data, discrimination that arises from bias and access to the SIS and their outcomes.
Journal ArticleDOI
Application of artificial neural network optimization for resilient ceramic parts fabricated by direct ink writing
Journal ArticleDOI
Hybrid Neural Network Cerebellar Model Articulation Controller Design for Non-linear Dynamic Time-Varying Plants.
TL;DR: This study proposes a hybrid method to control dynamic time-varying plants that comprises a neural network controller and a cerebellar model articulation controller (CMAC) and numerical-simulation results demonstrate the effectiveness of the proposed method.
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Journal ArticleDOI
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.