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
Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
TL;DR: The proposed work based on 744 segments of ECG signal is obtained from the MIT-BIH Arrhythmia database and can be applied in cloud computing or implemented in mobile devices to evaluate the cardiac health immediately with highest precision.
Journal ArticleDOI
Recommendation system based on deep learning methods: a systematic review and new directions
TL;DR: This paper is the first SLR specifically on the deep learning based RS to summarize and analyze the existing studies based on the best quality research publications and indicated that autoencoder models are the most widely exploited deep learning architectures for RS followed by the Convolutional Neural Networks and the Recurrent Neural Networks.
Journal ArticleDOI
Deep learning approach for microarray cancer data classification
TL;DR: A deep feedforward method to classify the given microarray cancer data into a set of classes for subsequent diagnosis purposes using a 7-layer deep neural network architecture having various parameters for each dataset is developed.
Journal ArticleDOI
Supervised learning in spiking neural networks: A review of algorithms and evaluations
TL;DR: This article presents a comprehensive review of supervised learning algorithms for spiking neural networks and evaluates them qualitatively and quantitatively, and provides five qualitative performance evaluation criteria and presents a new taxonomy for supervisedLearning algorithms depending on these five performance evaluated criteria.
Journal ArticleDOI
Non-iterative and Fast Deep Learning: Multilayer Extreme Learning Machines
TL;DR: A thorough review on the development of ML-ELMs, including stacked ELM autoencoder, residual ELM, and local receptive field based ELM (ELM-LRF), as well as address their applications, and the connection between random neural networks and conventional deep learning.
References
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Journal Article
Molecular computing: a review. I: Data and image storage
U. P. Wild,A. Renn +1 more
TL;DR: A review of spectral hole-burning and its application to data and image storage is presented in this paper, which is at present at the stage of a possible future technology and promises extremely high data storage capacities through its wavelength multiplexing property.
Book ChapterDOI
A New Concept for Parallel Neurocomputer Architectures
Alfred Strey,N. Avellana +1 more
TL;DR: This paper presents a new concept for a parallel neurocomputer architecture which is based on a configurable neuroprocessor design that adapts its internal parallelism dynamically to the required data precision for achieving an optimal utilization of the available hardware resources.
Journal ArticleDOI
Implementing plastic weights in neural networks using low precision arithmetic
TL;DR: The proposed design of an exponentially weighted moving average that is used in a neural network with plastic weights offers greatly improved memory and computational efficiency compared to a naive implementation of the EWMA's difference equation, and is well suited for implementation in digital hardware.
Journal ArticleDOI
An agent-based simulator driven by variants of Self-Organizing Maps
TL;DR: An agent-based simulator driven by variants of Self-Organizing Maps, specifically designed to model agents learning in economic systems, as well as to render how they interact and the way such interaction can affect the system general behavior is introduced.
Journal ArticleDOI
Architectures of neural networks applied for LVCSR language modeling
TL;DR: The aim of the presented work is to create a language module for the Polish language with the application of neural networks, and the capabilities of Kohonen's Self-Organized Maps will be explored to find the associations between words in spoken utterances.