Neurocomputing, Volume 56

Volume 56, January 2004

• Ajith Abraham:
  Meta learning evolutionary artificial neural networks. 1-38
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• Enrico Capobianco:
  On support vector machines and sparse approximation for random processes. 39-60
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• S. Rajasekaran, R. Amal Raj:
  Image recognition using analog-ART1 architecture augmented with moment-based feature extractor. 61-77
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• Christian Ziegaus, Elmar Wolfgang Lang:
  A neural implementation of the JADE algorithm (nJADE) using higher-order neurons. 79-100
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• Ping Guo, Michael R. Lyu:
  A pseudoinverse learning algorithm for feedforward neural networks with stacked generalization applications to software reliability growth data. 101-121
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• Chen-Chia Chuang, Jin-Tsong Jeng, Pao-Tsun Lin:
  Annealing robust radial basis function networks for function approximation with outliers. 123-139
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• Bruno Gas, Jean-Luc Zarader, Cyril Chavy, Mohamed Chetouani:
  Discriminant neural predictive coding applied to phoneme recognition. 141-166
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• Machiel Westerdijk, Wim Wiegerinck:
  Improving classification with latent variable models by sequential constraint optimization. 167-185
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• Eric de Bodt, Marie Cottrell, Patrick Letrémy, Michel Verleysen:
  On the use of self-organizing maps to accelerate vector quantization. 187-203
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• Suraphan Thawornwong, David Enke:
  The adaptive selection of financial and economic variables for use with artificial neural networks. 205-232
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• Simone Fiori, Pietro Burrascano:
  One-unit 'rigid-bodies' learning rule for principal/independent component analysis with application to ECT-NDE signal processing. 233-255
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• Nicolás García-Pedrajas, Domingo Ortiz-Boyer, César Hervás-Martínez:
  Cooperative coevolution of generalized multi-layer perceptrons. 257-283
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• Orazio Giustolisi:
  Sparse solution in training artificial neural networks. 285-304
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• Yann Guermeur, Gianluca Pollastri, André Elisseeff, Dominique Zelus, Hélène Paugam-Moisy, Pierre Baldi:
  Combining protein secondary structure prediction models with ensemble methods of optimal complexity. 305-327
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• Fred Henrik Hamker:
  Predictions of a model of spatial attention using sum- and max-pooling functions. 329-343
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• Jani J. T. Lahnajärvi, Mikko Lehtokangas, Jukka Saarinen:
  Estimating movements of a robotic manipulator by hybrid constructive neural networks. 345-363
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• Willy Wriggers, Pablo Chacón, Julio A. Kovacs, Florence Tama, Stefan Birmanns:
  Topology representing neural networks reconcile biomolecular shape, structure, and dynamics. 365-379
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• Fabian J. Theis, Elmar Wolfgang Lang, Carlos García Puntonet:
  A geometric algorithm for overcomplete linear ICA. 381-398
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• Kay Chen Tan, H. J. Tang, Z. Yi:
  Global exponential stability of discrete-time neural networks for constrained quadratic optimization. 399-406
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• Tzu-Yu Liu, Jerome Yeh, Chien-Ming Chen, Yen-Tseng Hsu:
  A GreyART system for grey information processing. 407-414
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• Jian Yang, Alejandro F. Frangi, Jing-Yu Yang:
  A new kernel Fisher discriminant algorithm with application to face recognition. 415-421
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• Hugo Uchida Frausto, Jan G. Pieters:
  Modelling greenhouse temperature using system identification by means of neural networks. 423-428
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• Huafu Chen, Dezhong Yao:
  A composite ICA algorithm and the application in localization of brain activities. 429-434
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• Christian R. Huyck:
  Overlapping cell assemblies from correlators. 435-439
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• Xinshun Xu, Zheng Tang, Rong Long Wang, XuGang Wang:
  A new motion equation for the minimum vertex cover problem. 441-446
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• Pravin Chandra, Yogesh Singh:
  A case for the self-adaptation of activation functions in FFANNs. 447-454
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• XuGang Wang, Zheng Tang, Hiroki Tamura, Masahiro Ishii, W. D. Sun:
  An improved backpropagation algorithm to avoid the local minima problem. 455-460
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• Giorgio Valentini, Marco Muselli, Francesca Ruffino:
  Cancer recognition with bagged ensembles of support vector machines. 461-466
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• Zhenwei Shi, Huanwen Tang, Yiyuan Tang:
  A new fixed-point algorithm for independent component analysis. 467-473
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• Sang-Woo Ban, Minho Lee, Hyun Seung Yang:
  A face detection using biologically motivated bottom-up saliency map model and top-down perception model. 475-480
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• Jinwen Ma, Taijun Wang, Lei Xu:
  A gradient BYY harmony learning rule on Gaussian mixture with automated model selection. 481-487
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