Neural networks: An overview of early research, current frameworks and new challenges

被引:200
作者
Prieto, Alberto [1 ]
Prieto, Beatriz [1 ]
Martinez Ortigosa, Eva [1 ]
Ros, Eduardo [1 ]
Pelayo, Francisco [1 ]
Ortega, Julio [1 ]
Rojas, Ignacio [1 ]
机构
[1] Univ Granada, CITIC UGR, Dept Comp Architecture & Technol, E-18071 Granada, Spain
关键词
Neural modelling; Neural networks; Artificial neural networks; Learning algorithms; Neural hardware; Neural simulators; Applications of neural networks; Human Brain Project; Brain Initiative; INDEPENDENT COMPONENT ANALYSIS; BRAIN-COMPUTER INTERFACES; EVENT-DRIVEN SIMULATION; LEARNING ALGORITHM; BLIND SEPARATION; SPIKING NEURONS; PATTERN-RECOGNITION; STABILITY ANALYSIS; DIGITAL IMPLEMENTATION; MULTILAYER PERCEPTRONS;
D O I
10.1016/j.neucom.2016.06.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a comprehensive overview of modelling, simulation and implementation of neural networks, taking into account that two aims have emerged in this area: the improvement of our understanding of the behaviour of the nervous system and the need to find inspiration from it to build systems with the advantages provided by nature to perform certain relevant tasks. The development and evolution of different topics related to neural networks is described (simulators, implementations, and real-world applications) showing that the field has acquired maturity and consolidation, proven by its competitiveness in solving real-world problems. The paper also shows how, over time, artificial neural networks have contributed to fundamental concepts at the birth and development of other disciplines such as Computational Neuroscience, Neuro-engineering, Computational Intelligence and Machine Learning. A better understanding of the human brain is considered one of the challenges of this century, and to achieve it:as this paper goes on to describe, several important national and multinational projects and initiatives are marking the way to follow in neural-network research. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:242 / 268
页数:27
相关论文
共 400 条
  • [1] Meta learning evolutionary artificial neural networks
    Abraham, A
    [J]. NEUROCOMPUTING, 2004, 56 (1-4) : 1 - 38
  • [2] OPTICAL NEURAL COMPUTERS
    ABUMOSTAFA, YS
    PSALTIS, D
    [J]. SCIENTIFIC AMERICAN, 1987, 256 (03) : 88 - 95
  • [3] ACKLEY DH, 1985, COGNITIVE SCI, V9, P147
  • [4] Ligand - based virtual screening procedure for the prediction and the identification of novel β-amyloid aggregation inhibitors using Kohonen maps and Counterpropagation Artificial Neural Networks
    Afantitis, Antreas
    Melagraki, Georgia
    Koutentis, Panayiotis A.
    Sarimveis, Haralambos
    Kollias, George
    [J]. EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY, 2011, 46 (02) : 497 - 508
  • [5] CHAOTIC NEURAL NETWORKS
    AIHARA, K
    TAKABE, T
    TOYODA, M
    [J]. PHYSICS LETTERS A, 1990, 144 (6-7) : 333 - 340
  • [6] Multilayer feedforward neural network based on multi-valued neurons (MLMVN) and a backpropagation learning algorithm
    Aizenberg, Igor
    Moraga, Claudio
    [J]. SOFT COMPUTING, 2007, 11 (02) : 169 - 183
  • [7] Akay M., 2007, Handbook of Neural Engineering
  • [8] An Organic Nanoparticle Transistor Behaving as a Biological Spiking Synapse
    Alibart, Fabien
    Pleutin, Stephane
    Guerin, David
    Novembre, Christophe
    Lenfant, Stephane
    Lmimouni, Kamal
    Gamrat, Christian
    Vuillaume, Dominique
    [J]. ADVANCED FUNCTIONAL MATERIALS, 2010, 20 (02) : 330 - 337
  • [9] Experimental neural networks for prediction and identification
    Alippi, C
    Piuri, V
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 1996, 45 (02) : 670 - 676
  • [10] CORPORATE DISTRESS DIAGNOSIS - COMPARISONS USING LINEAR DISCRIMINANT-ANALYSIS AND NEURAL NETWORKS (THE ITALIAN EXPERIENCE)
    ALTMAN, EI
    MARCO, G
    VARETTO, F
    [J]. JOURNAL OF BANKING & FINANCE, 1994, 18 (03) : 505 - 529