Palavraschave: Hopfield net, convergence, discrete time systems

165A novel adaptive filtering technique for the processing of abdominal fetal electrocardiogram using neural network
Selvan, S.; Srinivasan, R.
Adaptive Systems for Signal Processing, Communications, and Control Symposium 2000.
ASSPCC. The IEEE 2000 , 2000
Page(s): 289 –292
Palavraschave: adaptive filtering, fetal eletrogrardiogram,


166A recurrent neural network for minimum infinitynorm kinematic control of redundant manipulators with an improved problem formulation and reduced architecture complexity
Wai Sum Tang; Jun Wang
Systems, Man and Cybernetics, Part B, IEEE Transactions on , Volume: 31 Issue: 1 ,
Feb 2001
Page(s): 98 –105
Palavraschave:kinematic control, control,redundant manipulators


167A recurrent neural network for online design of robust optimal filters
Danchi Jiang; Jun Wang
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on ,
Volume: 47 Issue: 6 , June 2000
Page(s): 921 –926
Palavraschave:circuits, filters, optmal filters


168A spatio temporal neural network on dynamic Gdenhanced MR images for diagnosing recurrent nasal papilloma
ChuanYu Chang; PauChoo Chung; ELiang Chen; WenChen Huang; PingHong Lai
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual
International Conference of the IEEE , Volume: 4 , 2000
Page(s): 3056 3059 vol.4
Palavraschave: spatio temporal, dynamic Gd enhanced, MR images


169A truncated normalized max product set of equations and its solution for a recurrent fuzzy neural network
Brouwer, R.K.
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th ,
Volume: 1 , 2001
Page(s): 529 –533
Palavraschave:fuzzy, truncated normalized max product


170Adaptive control for multimachine power systems using genetic algorithm and neural network
Senjyu, T.; Yamane, S.; Uezato, K.
Power Engineering Society Winter Meeting, 2000. IEEE , Volume: 2 , 2000
Page(s): 1342 1347 vol.2
Palavraschave:power engineering, adaptive systems, genetic algorithms,


172Adaptive hybrid control using recurrentneuralnetwork for linear synchronous motor servo drive system
FaaJeng Lin; WenDer Chou; ChihHong Lin
Electrical and Computer Engineering, 2001. Canadian Conference on , Volume: 1 , 2001
Page(s): 643 –648
Palavraschave:control, adaptive systems, servo drive system


173Adaptive recurrentneuralnetwork control for linear induction motor
RongJong Wai; ChunMing Hong
Control Applications, 2000. Proceedings of the 2000 IEEE International Conference on ,
2000
Page(s): 184 –189
Palavraschave:control, induction motor, linear induction


174An artificial neural network model for generating periodic signals by synchronizing external stimuli
Fujimoto, K.; Cottenceau, G.; Akutagawa, M.; Nagashino, H.; Kinouchi, Y.
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual
International Conference of the IEEE , Volume: 3 , 2000
Page(s): 1909 1912 vol.3
Palavraschave:periodic signals, symchronizing stimuli


175An evolutionary activevision system
Kato, T.; Floreano, D.
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on , Volume: 1 ,
2001
Page(s): 107 114 vol. 1
Palavraschave:evolutionary, active system,


176A trial activity enhancement by Wiener filtering using an artificial neural network
Vasquez, C.; Hernandez, A.; Mora, F.; Carrault, G.; Passariello, G.
Biomedical Engineering, IEEE Transactions on , Volume: 48 Issue: 8 , Aug. 2001
Page(s): 940 –944
Palavraschave:wiener filtering, biomedical applications, Wiener


177Combined identification of parameters and nonlinear characteristics based on inputoutput data
Hintz, C.; Rau, M.; Schroder, D.
Advanced Motion Control, 2000. Proceedings. 6th International Workshop on , 2000
Page(s): 175 180
Palavraschave:paramete identification, non linear systems, control


178Contactless magnetic leadscrew: vibration control and resonance
compensation
Chang, T.; Dani, B.; Zhiming Ji; Caudill, R.
American Control Conference, 2000. Proceedings of the 2000 , Volume: 3 , 2000
Page(s): 2087 2091 vol.3
Palavraschave:control, vibration, ressonance


179Dynamic wavelet neural network for nonlinear dynamic system identification
Yonghong Tan; Xuanju Dang; Feng Liang; ChunYi Su
Control Applications, 2000. Proceedings of the 2000 IEEE International Conference on ,
2000
Page(s): 214 –219
Palavraschave:wavelet, non linear systems, system identification


180Emergence of horizontal cells receptive fields spectral properties by decorrelation of cones spectral response functions
Iniushin, M.U.; Stankevich, A.A.
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on ,
Volume: 1 , 2001
Page(s): 99 102 vol.1
Palavraschave:spectral response, correlation


181Enhancement of QRS complex using a neural network based ALE
HanGo Choi; EunBo Shim
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual
International Conference of the IEEE , Volume: 2 , 2000
Page(s): 958 961 vol.2
Palavraschave:biology, QRS, ALE


182Generation of the sense of a sentence in Arabic language with a connectionist approach
Meftouh, K.; Laskri, M.T.
Computer Systems and Applications, ACS/IEEE International Conference on. 2001 ,
2001
Page(s): 125 –127
Palavraschave:language, connection aproach recurrent neural net.


183Generation scheduling with demand bids
Sheridan, W.P.; Flynn, M.E.; O'Malley, M.J.
Power Engineering Society Summer Meeting, 2000. IEEE , Volume: 4 , 2000
Page(s): 2109 2114 vol. 4
Palavraschave:power systems, schedulind, demand bids


184Global stability analysis of discretetime recurrent neural networks
Barabanov, N.E.; Prokhorov, D.V.
American Control Conference, 2001. Proceedings of the 2001 , Volume: 6 , 2001
Page(s): 4550 –4555
Palavraschave: stability analysis, control


185High speed directional element design and evaluation using neurocomputing technology
SanayePasand, M.; Malik, O.P.
Developments in Power System Protection, 2001, Seventh International Conference on
(IEE) , 2001
Page(s): 291 –294
Palavraschave:power systems, control


186Hybrid control for speed sensorless induction motor drive
RongJong Wai
Fuzzy Systems, IEEE Transactions on , Volume: 9 Issue: 1 , Feb 2001
Page(s): 116 –138
Palavraschave:control, induction motor, fuzzy


187Hybrid control using recurrent fuzzy neural network for linear induction motor servo drive
FaaJeng Lin; RongJong Wai
Fuzzy Systems, IEEE Transactions on , Volume: 9 Issue: 1 , Feb 2001
Page(s): 102 –115
Palavraschave:control, fuzzy, linear induction motor


188Identification of a nonlinear multi stand rolling system by a structured recurrent neural network
Hintz, C.; Rau, M.; Schroder, D.
Industry Applications Conference, 2000. Conference Record of the 2000 IEEE , Volume:
2 , 2000
Page(s): 1121 1128 vol.2
Palavraschave:non linear systems


189Identification of dynamic systems using recurrent fuzzy neural network
ChihMin Lin; ChunFei Hsu
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th , 2001
Page(s): 2671 –2675
Palavraschave:dynamic systems, identification systems, fuzzy


190Intelligent backstepping control for linear induction motor drive
Wai, R.J.; Lin, F.J.; Hsu, S.P.
Control Theory and Applications, IEE Proceedings , Volume: 148 Issue: 3 , May 2001
Page(s): 193 –202
Palavraschave:control, motor, linear induction


191Intelligent modeling, observation, and control for nonlinear systems
Schroder, D.; Hintz, C.; Rau, M.
Mechatronics, IEEE/ASME Transactions on , Volume: 6 Issue: 2 , June 2001
Page(s): 122 –131
Palavraschave: control, non linear systems, artificial intelligence

192 A Learning Algorithm for Continually Running Fully Connected Recurrent Neural Networks
R. J. Williams and D. Zipser
Technical Report, Un. of California at San Diego, Number ICS8805, 1988.
Palavraschave: learning,

193 Application of temporal neural networks to source localisation
B. Colnet and S. Durand
International Conference on Artificial Neural Networks and Genetic Algorithms, April 1995.
Palavraschave: genetic, evolutionary, source localization

194 A Method for Training Recurrent Neural Networks for Classification by Building Basins of Attraction
R. K. Brouwer
Neural Networks, 8(4), pp. 597603, 1995.
Palavraschave: training, classification, atraction

195  Alopex: A CorrelationBased Learning Algorithm for FeedForward and Recurrent Neural Networks
K. P. Unnikrishnan and K. P. Venugopal
Neural Computation, 6(3), pp. 469490, 1994.
Palavraschave: learning alg., feedforward neural nets

196 An algebraic framework to represent finite state automata in singlelayer recurrent neural networks
R. Alquezar and A. Sanfeliu
Neural Computation, 7(5), pp. 931949, 1995.
Palavraschave: control, finite state automata, single layer

197 Absolute Stability Conditions for DiscreteTime Recurrent Neural Networks
Liang Jin and Peter N. Nikiforuk and Madan M. Gupta
IEEE Transactions on Neural Networks, 5(6), pp. 954964, November 1994.
Palavraschave: stability, discrete time, recurrent

198 Adding Learning to Cellular Genetic Algorithms for Training Recurrent Neural Networks
K. W. C. Ku and M. W. Mak and W. C. Siu
IEEENN, 10(2), p. 239, March 1999.
Palavraschave: learning, genetic, evolutionary

199 A Fixed Size Storage Time Complexity Learning Algorithm for Fully Recurrent Continually Running Networks
J. H. Schmidhuber
Neural Computation, 4(2), pp. 243248, 1992.
Palavraschave: learning, storage

200  A Framework of Combining Symbolic and Neural Learning
J. W. Shavlik
Technical Report, Computer Sciences Dept, U of Wisconson  Madison, Number TR 1123, Computer Sciences Dept., 1992.
Palavraschave: learning, symbolic, recurrent

201 A Learning Algorithm for Adaptive TimeDelays in a Temporal Neural Network
D. T. Lin and J. E. Dayhoff and P. A. Ligomenides
Technical Report, Systems Research Center, University of Maryland, Number TR 9259, 1992.
Palavraschave: learning, adaptive systems, time delay

202 A learning algorithm for Boltzmann Machines
D. H. Ackley and G. E. Hinton and T. J. Sejnowski
Cognitive Science, Vol. 9, pp. 147169, 1985.
Palavraschave: learning, boltzman machines

203 A Convergence Theorem for Sequential Learning in TwoLayer Perceptrons
M. Marchand and M. Golea and P. Rujan
Europhysics Letters, Vol. 11, p. 487, 1990.
Palavraschave: convergence, sequential, learning

204 A Learning Method for Recurrent Networks Based on Minimization of Finite Automata
I. Noda and M. Nagao
Proceedings International Joint Conference on Neural Networks 1992, Vol. I, pp. 2732, June 1992. Palavraschave: learning, automata , finite automata

205 A learning Rule for Asynchornous Perceptrons with Feedback in a Combinatorial Environment
L. B. Almeida
IEEE First Int. Conf. Neural Networks, pp. 609618, 1987.
Palavraschave: learning, asyncronous, feedback

206 A Method for Constructive Learning of Recurrent Neural Networks
D. Chen and C. L. Giles and G. Z. Sun and H. H. Chen and Y. C. Lee and M. W. Goudreau
Computational Learning Theory and Natural Learning Systems III, pp. 95114, MIT Press, 1995.
Palavraschave: learning, construtive learning, method

207 A Neural Model for Category Learning
D. L. Reilly and L. N. Cooper and C. Elbaum
Biological Cybernetics, Vol. 45, pp. 3541, 1982.
Palavraschave: learning, category, model

208 A Survey And Critique of Techniques For Extracting Rules From Trained Artificial Neural Networks
R. Andrews and J. Diederich and A. B. Tickle
Technical Report, Queensland University of Technology, Number QUTNRC950102, 1995.
Palavraschave: survey, supervised, extracting rules

209 A Unified Approach for Integrating Explicit Knowledge and Learning by Example in Recurrent Networks
P. Frasconi and M. Gori and M. Maggini and G. Soda
1991 IEEE INNS International Joint Conference on Neural Networks  Seattle, Vol. 1, pp. 811816, IEEE Press, 1991.
Palavraschave: learning, example, knowledge

210 An Algebraic Framework to Represent Finite State Machines in SingleLayer Recurrent Neural Networks
R. Alquézar and A. Sanfeliu
Neural Computation, 7(5), pp. 931949, 1995.
Palavraschave: finite state machine, algebric, single layer

211 An Analysis of Noise in Recurrent Neural Networks: Convergence and Generalization
K.C. Jim and C. L. Giles and B. G. Horne
IEEE Transactions on Neural Networks, 7(6), pp. 14241438, November 1996.
Palavraschave: noise, convergence, generalization

212 An Analysis of the Gamma Memory in Dynamic Neural Networks
J. C. Principe and J. M. Kuo and S. Celebi
IEEE Transactions on Neural Networks, 5(2), pp. 331337, 1994.
Palavraschave: gamma memory, memory, dynamical systems

213 Associative Memory in a Simple Model of Oscillating Cortex
Bill Baird
Advances in Neural Information Processing Systems 2, pp. 6875, Morgan Kaufmann Publishers, 1990.
Palavraschave: memory, associative memory, model

214 Application of temporal neural networks to source localisation
B. Colnet and S. Durand
International Conference on Artificial Neural Networks and Genetic Algorithms, April 1995.
Palavraschave: temporal, source localization

215 Biases in Inductive Learning: Introduction
Diana Gordon
Proceedings of the Machine Learning 1992 Workshop on Biases in Inductive Learning, 1992.
Palavraschave: learning, bias, inductive learning

216 BlockStructured Recurrent Neural Networks
S. Santini and Del A. Bimbo and R. Jain
Neural Networks, 8(1), pp. 135147, 1995.
Palavraschave: architeture, structured

217 Can Recurrent Neural Networks Learn Natural Language Grammars?
Steve Lawrence and C. Lee Giles and Sandiway Fong
Proceedings of the IEEE International Conference on Neural Networks, pp. 18531858, IEEE Press, 1996.
Palavraschave: grammar, language , learning

218 Constructing deterministic finitestate automata in sparse recurrent neural networks
C. W. Omlin and C. L. Giles
IEEE International Conference on Neural Networks (ICNN'94), pp. 17321737, IEEE Press, 1994.
Palavraschave: control, finitestate autonoma, sparse recurrente neural nets

219  Constructive Learning of Recurrent Neural Networks
D. Chen and C. Lee Giles and G. Z. Sun and H. H. Chen and Y. C. Lee and M. W. Goudreau
Computational Learning Theory and Natural Learning Systems III, MIT Press, 1993.
Palavraschave: learning, constructive

220  Constructive Learning of Recurrent Neural Networks: Limitations of Recurrent Casade Correlation and a Simple Solution
C. L. Giles and D. Chen and G. Z. Sun and H. H. Chen and Y. C. Lee and M. W. Goudreau
IEEE Transactions on Neural Networks, 1994.
Palavraschave: Learning, control, cascade correlation

221 Can Recurrent Neural Networks Learn Natural Language Grammars?
Steve Lawrence and C. Lee Giles and Sandiway Fong
Proceedings of the IEEE International Conference on Neural Networks, pp. 18531858, IEEE Press, 1996.
Palavraschave: learning, grammar, language

222 Computational capabilities of recurrent NARX neural networks
H. T. Siegelmann and B. G. Horne and C. L. Giles
Technical Report, University of Maryland Department of Computer Science, Number UMIACSTR9512 and CSTR3408, 1995.
Palavraschave: NARX, capabilities

223 Constructive Learning of Recurrent Neural Networks
D. Chen and C. Lee Giles and G. Z. Sun and H. H. Chen and Y. C. Lee and M. W. Goudreau
Computational Learning Theory and Natural Learning Systems III, MIT Press, 1993.
Palavraschave: learning, learning systems

224 Credit assignment through Time: Alternatives to Backpropagation
Yoshua Bengio and P. Frasconi
Advances in Neural Information Processing Systems 6, Morgan Kaufmann, 1994.
Palavraschave: time, backpropagation, recurrent

225 Combining Symbolic and Neural Learning
J. W. Shavlik
Machine Learning, 14(3), pp. 321331, 1994.
Palavraschave: symbol, learning, combining

226 Comments on ``Constructive Learning of Recurrent Neural Networks: ...'', Cascading the Proof Describing Limitations of Recurrent Cascade Correlation
S. C. Kremer
IEEE Transactions on Neural Networks, 1996.
Palavraschave: learning, construtive learning, limitations

227 Comments On ``Diagonal Recurrent Neural Networks for Dynamic Systems Control''Reproof of Theorems 2 and 4
X. Liang
IEEE Transactions on Neural Networks, 8(3), pp. 811812, May 1997.
Palavraschave: comments, diagonal neural net, dynamic systems, control

228 Complexity of exact gradient computation algorithms for recurrent neural networks
R. J. Williams 
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