Table of Contents

• Learning algorithms for adaptive processing and controlBernard Widrow, Michael A. Lehr, Françoise Beaufays, Eric A. Wan, Michel Bilello. 1-8 [doi]
• Multiple networks for function learningEthem Alpaydin. 9-14 [doi]
• A universal structure for artificial neural networksFawad Rauf, Hassan M. Ahned. 15-20 [doi]
• Back-propagation algorithm with controlled oscillation of weightsYolanda M. Pires, Dilip Sarkar. 21-26 [doi]
• Parallel consensual neural networksJón Atli Benediktsson, Johannes R. Sveinsson, Okan K. Ersoy, Philip H. Swain. 27-32 [doi]
• Self-clustering recurrent networksZheng Zeng, Rodney M. Goodman, Padhraic Smyth. 33-38 [doi]
• Hopf bifurcation and Hopf hopping in recurrent netsFu-Sheng Tsung, Garrison W. Cottrell. 39-45 [doi]
• On design and evaluation of tapped-delay neural network architecturesClaus Svarer, Lars Kai Hansen, Jan Larsen. 46-51 [doi]
• A hybrid technique to enhance the performance of recurrent neural networks for time series predictionSathyanarayan S. Rao, Viswanath Ramamurti. 52-57 [doi]
• Synaptic coding of periodically modulated spike trainsJosé Pedro Segundo, Jean-François Vibert, Michael Stiber, S. Hanneton. 58-63 [doi]
• Temporal competition as an optimal parallel processing of the cerebrohypothalamic systemKiyohiko Nakamura. 64-69 [doi]
• A spatio-temporal neural network model of saccade generationKuniharu Arai, Edward L. Keller, Jay A. Edelman. 70-74 [doi]
• Dynamics of synaptic transfer in living and simulated neuronsMichael Stiber, José Pedro Segundo. 75-80 [doi]
• Solving search problems with subgoals using an artificial neural networkPing Liang, Kai Jin. 81-86 [doi]
• Solving the serializability problem by a connectionist machineMert Sungur, Ugur Halici. 87-92 [doi]
• Classification of Parkinson rating-scale-data using a selforganising neural netThomas Fritsch, P. H. Kraus, H. Przuntek, Phuoc Tran-Gia. 93-98 [doi]
• Solving inverse problems in nonlinear PDEs by recurrent neural networksTadasu Uchiyama, Noboru Sonehara. 99-102 [doi]
• Force directed self-organizing map and its application to VLSI cell placementRay-I Chang, Pei-Yung Hsiao. 103-109 [doi]
• The effects of analog hardware properties on backpropagation networks with on-chip learningBrion K. Dolenko, Howard C. Card. 110-115 [doi]
• An analog VLSI model of central pattern generation in the medicinal leechMicah S. Siegel. 116-119 [doi]
• Analog neural networks solve ambiguity problems in medium PRF radar systemsChia-Jiu Wang, Chwan-Hwa John Wu. 120-125 [doi]
• Stereo correspondence through multiple constraint neural networksJoe-E Hu, Pepe Siy. 126-131 [doi]
• A neural network based edge detectorKamran Etemad, Rama Chelappa. 132-137 [doi]
• A cortical structure for real world image processingJörg Kopecz. 138-143 [doi]
• A distributed adaptive control system for a quadruped mobile robotBruce L. Digney, Madan M. Gupta. 144-149 [doi]
• Sensorimotor coordination and sensor fusion by neural networksGuo-Qing Wei, Gerd Hirzinger, Bernhard Brunner. 150-155 [doi]
• Motion controls using complex-valued neural networks with feedback loopsAkira Hirose. 156-161 [doi]
• On self-consistent sensory-motor learning algorithmShengfa Hu, Pingfan Yan, Yanda Li. 162-167 [doi]
• Efficient learning and planning within the Dyna frameworkJing Peng, Ronald J. Williams. 168-174 [doi]
• Exploration and model building in mobile robot domainsSebastian Thrun. 175-180 [doi]
• Hierarchical learning of robot skills by reinforcementLong Ji Lin. 181-186 [doi]
• Monaural localization using combination of TD ( lambda ) with backpropagationLichun Wang, P. N. Denbigh. 187-190 [doi]
• Performance improvement of machine learning via automatic discovery of facilitating functions as applied to a problem of symbolic system identificationJohn R. Koza, Martin A. Keane, James P. Rice. 191-198 [doi]
• Design architectures and training of neural networks with a distributed genetic algorithmShai Oliker, Merrick L. Furst, Oded Maimon. 199-202 [doi]
• Use of genetic algorithms with backpropagation in training of feedforward neural networksMichael McInerney, Atam P. Dhawan. 203-208 [doi]
• Coordinative behavior in evolutionary multi-agent system by genetic algorithmTakanori Shibata, Toshio Fukuda. 209-214 [doi]
• Sensitivity analysis for input vector in multilayer feedforward neural networksLi Fu, Tinghuai Chen. 215-218 [doi]
• Minimum entropy methods in neural networks: competition and selective responses by entropy minimizationRyotaro Kamimura. 219-225 [doi]
• A dynamic neural network architecture by sequential partitioning of the input spaceR. S. Shadafan, M. Niranjan. 226-231 [doi]
• Geometric error correction using hierarchical/hybrid artificial neural systemsJa C. Koo, Benito Fernández. 232-237 [doi]
• A rule based prototype system for automatic classification in industrial quality controlSaman K. Halgamuge, Werner Pöchmüller, Manfred Glesner. 238-243 [doi]
• Learning strategies for an adaptive information retrieval system using neural networksFabio Crestani. 244-249 [doi]
• Pruning and rule extraction using class entropySandro Ridella, Gian Luca Speroni, Paolo Trebino, Rodolfo Zunino. 250-256 [doi]
• Annealing networks and fractal landscapesRaymond Lister. 257-262 [doi]
• A quick algorithm of neural combinatorial optimization to data association problem of multimaneuvering target trackingZhongliang Jing, Guawei Zhang, Hongren Zhou. 263-268 [doi]
• Improved kick out learning algorithm with delta-bar-delta-bar ruleKeihiro Ochiai, Shiro Usui. 269-274 [doi]
• Solving the scheduling problem in high level synthesis using a normalized mean field neural networkM. Kemal Unaltuna, Mehmet Emin Dalkiliç, Vijay Pitchumani. 275-280 [doi]
• Meaning-based handling of don't care attributes in artificial neural networksNadine N. Tschichold-Gürman, Vlad G. Dabija. 281-286 [doi]
• Hierarchical ensemble of neural networksPinaki Poddar, P. V. S. Rao. 287-292 [doi]
• Optimal Brain Surgeon and general network pruningBabak Hassibi, David G. Stork, Gregory J. Wolff. 293-299 [doi]
• Discriminant analysis neural networksJianchang Mao, Anil K. Jain 0001. 300-305 [doi]
• Neuro-fuzzy optimal control of backing up a trailer truckHidetomo Ichihashi, M. Tokunaga. 306-311 [doi]
• FUN: optimization of fuzzy rule based systems using neural networksSandra Sulzberger, Nadine N. Tschichold-Gürman, Sjur J. Vestli. 312-316 [doi]
• Implementation of fuzzy systems using multilayered neural networkHiroshi Narazaki, Anca L. Ralescu. 317-322 [doi]
• Supervised fuzzy ART: training of a neural network for pattern classification via combining supervised and unsupervised learningHahn-Ming Lee, Chia-Shing Lai. 323-328 [doi]
• A ClusNet architecture for predictionWilliam H. Hsu, Loke-Soo Hsu, Manoel Fernando Tenorio. 329-334 [doi]
• A chaotic neural unitAlison A. Dingle, John H. Andreae, Richard D. Jones. 335-340 [doi]
• A Bayesian interpretation for the Hopfield networkEdwin R. Hancock, Josef Kittler. 341-346 [doi]
• Hybrid location-content addressable memoryBo-Hyeun Wang, Seak Bai Koh, Seung Kwon Ahn. 347-352 [doi]
• Retrieval process of an associative memory with nonmonotonic input-output functionHidetoshi Nishimori, Ioan Opris. 353-358 [doi]
• A temporal memory network with state-dependent thresholdsJoydeep Ghosh, Shaoyun Wang. 359-364 [doi]
• Calculus relations in spatial summation and determination of macro connection in neuronal networksC. N. Zhang, M. Wang, G. Z. Yao. 365-370 [doi]
• Some notes on perceptron learningMarco Budinich. 371-376 [doi]
• Extension of approximation capability of three layered neural networks to derivativesYoshifusa Ito. 377-381 [doi]
• Noninvertibility in neural networksRamiro Rico-Martínez, Ioannis G. Kevrekidis, Raymond A. Adomaitis. 382-386 [doi]
• A neural network isolated word recognition system for moderate sized databasesJianping Huang, Anthony Kuh. 387-391 [doi]
• Identification of human faces through texture-based feature recognition and neural network technologyMarijke F. Augusteijn, Tammy L. Skufca. 392-398 [doi]
• Inverse recall neural network model and feedback pattern recognitionKeiji Yamada. 399-406 [doi]
• A neural network that embeds its own meta-levelsJürgen Schmidhuber. 407-412 [doi]
• A neural network model for real-time adaptive clusteringLiMin Fu. 413-416 [doi]
• The self-organizing reduced kernel density estimatorLasse Holmström, Ari Hämäläinen. 417-421 [doi]
• Bayesian case-based reasoning with neural networksPetri Myllymäki, Henry Tirri. 422-427 [doi]
• Construction of neural networks for piecewise approximation of continuous functionsChong-Ho Choi, Jin-Young Choi. 428-433 [doi]
• Identification of unknown categories with probabilistic neural networksT. P. Washburne, D. F. Specht, R. M. Drake. 434-437 [doi]
• Unknown parameter identification of parameterized system using multi-layered neural networkSung Woo Kim, Ju-Jang Lee. 438-443 [doi]
• Scalability in neural network design: an add-on schemeH. Chris Tseng, J. Gary Liu. 444-449 [doi]
• Incremental grid growing: encoding high-dimensional structure into a two-dimensional feature mapJustine Blackmore, Risto Miikkulainen. 450-455 [doi]
• A connectionist approach for default inference and conflict resolutionHiroshi Zarazaki, Anca L. Ralescu. 456-461 [doi]
• Recursive neural networks with high capacityChang-Jiu Chen, John Y. Cheung. 462-465 [doi]
• A quickly trained ANN with single hidden layer Gaussian unitsGoutam Chakraborty, Norio Shiratori, Shoichi Noguchi. 466-472 [doi]
• Non-monotonic firing rate of a coupled FitzHugh-Nagumo modelYo Horikawa. 473-478 [doi]
• Design of adaptive and incremental feed-forward neural networksHown-Wen Chen, Von-Wun Soo. 479-484 [doi]
• A theory of over-learning in the presence of noiseKazutaka Yamasaki, Hidemitsu Ogawa. 485-488 [doi]
• Sigma-delta modulation neural networksKwan F. Cheung, Patrick Y. H. Tang. 489-493 [doi]
• Training of neural network classifier by combining hyperplane with exemplar approachHahn-Ming Lee, Weng-Tang Wang. 494-499 [doi]
• Using spectral techniques for improved performance in artificial neural networksBruce E. Segee. 500-505 [doi]
• Performance measures for neural nets using Johnson distributionsWilliam C. Torrez, Jayson T. Durham, Richard D. Trueblood. 506-510 [doi]
• Experimental analysis of input weight freezing in constructive neural networksJames Tin-Yau Kwok, Dit-Yan Yeung. 511-516 [doi]
• Use of fractional powers to moderate neuronal contributionsDonna L. Hudson, Maurice E. Cohen. 517-522 [doi]
• Gaussian network variants: a preliminary studyStephen J. Koffman, Peter H. Mechl. 523-528 [doi]
• MRAC of nonlinear systems using neural networks with recursive least squares adaptationK. F. Fong, A. P. Loh. 529-533 [doi]
• A rule-based neural controller for inverted pendulum systemJianbin Hao, Shaohua Tan, Joos Vandewalle. 534-539 [doi]
• Neural network-based robot trajectory generationDan Simon. 540-545 [doi]
• Time optimal control using pi-sigma networksKunio Iwata, Joydeep Ghosh, Yoan Shin. 546-551 [doi]
• Neuromorphic self-tuning PID controllerSaiful Akhyar, Sigeru Omatu. 552-557 [doi]
• Dynamic neural controller with somatic adaptationD. H. Rao, Madan M. Gupta. 558-563 [doi]
• Identification of a nonlinear multivariable dynamic process using feed-forward networksCan Isik, A. Mete Çakmakci. 564-567 [doi]
• Identification of a PUMA-560 two-link robot using a stable neural networkChris M. Jubien, Nikitas J. Dimopoulos. 568-572 [doi]
• An improved learning law for backpropagation networksSu Zhou, Dobrivoje Popovic, Günter Schulz-Ekloff. 573-579 [doi]
• Acceleration of back propagation through initial weight pre-training with delta ruleGang Li, Hussein Alnuweiri, Yuejian Wu, Hongbing Li. 580-585 [doi]
• A direct adaptive method for faster backpropagation learning: the RPROP algorithmMartin Riedmiller, Heinrich Braun. 586-591 [doi]
• Backpropagation using generalized least squaresA. P. Loh, K. F. Fong. 592-597 [doi]
• Initializations, back-propagation and generalization of feed-forward classifiersWouter F. Schmidt, Sarunas Raudys, Martin A. Kraaijveld, Marina Skurikhina, Robert P. W. Duin. 598-604 [doi]
• Supervised learning for feed-forward neural networks: a new minimax approach for fast convergenceAntonio Chella, Antonio Gentile, Filippo Sorbello, A. Tarantino. 605-609 [doi]
• Fuzzy logic controllers: from development to deploymentPiero P. Bonissone, Kenneth H. Chiang. 610-619 [doi]
• Simple addition to back-propagation learning for dynamic weight pruning, sparse network extraction and faster learningMalcolm I. Heywood, Peter Noakes. 620-625 [doi]
• Adaptive k-means algorithm with error-weighted deviation measureChedsada Chinrungrueng, Carlo H. Séquin. 626-631 [doi]
• A multi-template learning method based on LVQAtsushi Sato, Keiji Yamada, Jun Tsukumo. 632-637 [doi]
• Object separation in dynamic neural networksHerbert J. Reitboeck, Michael Stöcker, Christoph Hahn. 638-641 [doi]
• Neuroanatomy of neural networks of the vestibular system: vestibular maculas as prototypic neuronal networksMuriel D. Ross. 642-647 [doi]
• Artificial cerebellum ACE: tensor network transformer enabling virtual movement in virtual environment: facilitating teleoperation in telepresenceAndras J. Pellionisz, David L. Tomko, Charles C. Jorgensen. 648-654 [doi]
• A sensory information processing system using neural networksDaiki Masumoto, Takashi Kimoto, Shigemi Nagata. 655-660 [doi]
• Preserving visual perception by learning natural clusteringWillie Chang, Hamdy S. Soliman, Andrew H. Sung. 661-666 [doi]
• Bimodal sensor integration on the example of 'speechreading'Christoph Bregler, Stefan Manke, Hermann Hild, Alex Waibel. 667-671 [doi]
• Sensory fusion: integrating visual and auditory information for recognizing speechGregory J. Wolff. 672-677 [doi]
• A neural network approach to the consistent labeling problemJiansheng Feng, Wenjing Tao, Hans Burkhardt. 678-683 [doi]
• Visualizing weight dynamics in the N-2-N encoderRaymond Lister. 684-689 [doi]
• On-line sensing of drill wear using neural network approachT. I. Liu, K. S. Anantharaman. 690-694 [doi]
• Performance of a neural net scheduler used in packet switching interconnection networksManfred Mittler, Phuoc Tran-Gia. 695-700 [doi]
• Analog CMOS implementation of backward error propagationYiwen Wang. 701-706 [doi]
• Modular neural network hardware implementation of analog-digital mixed operationIl Song Han. 707-710 [doi]
• Stochastic arithmetic implementations of neural networks with in situ learningJeffrey A. Dickson, Robert D. McLeod, Howard C. Card. 711-716 [doi]
• A novel counter circuit using a multi-level neuron with a self-feedback weightJen-Dong Yuh, Robert W. Newcomb. 717-720 [doi]
• A two-stage neural net for segmentation of range imagesSugata Ghosal, Rajiv Mehrotra. 721-726 [doi]
• Image compression using topological maps and MLPGilles Burel, Jean-Yves Catros. 727-731 [doi]
• A neural network for perceptual grouping, based on architecture of the primary visual cortex, efficient for texture segregation in complex natural imagesJean-Luc Anton, Patrick Marchal, Yves Burnod. 732-736 [doi]
• Three applications of artificial neural networks for controlJudy A. Franklin. 737-742 [doi]
• Dynamic neural unit and function approximationD. H. Rao, Madan M. Gupta. 743-748 [doi]
• A neural controller for the tracking control of flexible armsW. Cheng, J. T. Wen. 749-754 [doi]
• A neural network architectural model of visual cortical cells for texture segregationGiacomo M. Bisio, Daniele D. Caviglia, Giacomo Indiveri, Luigi Raffo, Silvio P. Sabatini. 755-760 [doi]
• An algorithm of eye movement in selective fixationTohru Yagi, Kazutoshi Gouhara, Yoshiki Uchikawa. 761-765 [doi]
• A high level Petri net model of olfactory bulbKurapati Venkatesh, Oren Masory, Abhijit Pandya. 766-771 [doi]
• Low level modeling of the development of directionally selective microcircuits in cat striate cortexAndrew H. Fagg, József Fiser. 772-777 [doi]
• A fast supervised-learning algorithm for large, multilayered neural networksDonald L. Prados. 778-782 [doi]
• Robustness of feedforward neural networksChing-Tai Chiu, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka. 783-788 [doi]
• A fast supervised learning scheme for recurrent neural networks with application to associative memory designH. Chris Tseng, Victor H. Hwang, Ling Lu. 789-793 [doi]
• Task decomposition and competing expert system-artificial neural net objects for reliable and real time inferenceRajiv Khosla, Tharam S. Dillon. 794-800 [doi]
• Rule refinement with recurrent neural networksC. Lee Giles, Christian W. Omlin. 801-806 [doi]
• A neural production system and its application in visual-guided mobile robot navigationM. Meng. 807-812 [doi]
• A neural network solution for the correspondence problemJ. H. van Deemter, H. A. K. Mastebroek. 813-819 [doi]
• A neural network with Hebbian-like adaptation rules learning visuomotor coordination of a PUMA robotThomas Martinetz, Klaus Schulten. 820-822 [doi]
• NNP: a neural net classifier using prototypesChristine Decaestecker. 822 [doi]
• Synthesis of mechanical linkages using artificial neural networks and optimizationJosiah C. Hoskins, Glenn A. Kramer. 822 [doi]
• An integrated approach to cellular mobile communication planning using traffic data prestructured by a self-organizing feature mapThomas Fritsch, Stefan Hanshans. 822 [doi]
• A fault tolerant optimal interpolative netDan Simon, Hossny El-Sherief. 825-830 [doi]
• Derivation of momentum LMS algorithms by minimizing objective functionsBandula W. Dahanayake, A. R. M. Upton. 831-835 [doi]
• Global descent replaces gradient descent to avoid local minima problem in learning with artificial neural networksBedri C. Cetin, Joel W. Burdick, Jacob Barhen. 836-842 [doi]
• Recurrent neural networks for temporal learning of time seriesV. Sterzing, B. Schürmann. 843-850 [doi]
• Gradient computation in time delayed recurrent neural network with memory for static input-output mapping under stability constraintV. Chandrasekaran, Marimuthu Palaniswami, Terry M. Caelli. 851-856 [doi]
• A cascaded recurrent neural network for real-time nonlinear adaptive filteringLiang Li, Simon Haykin. 857-862 [doi]
• Evolving neural network connectivityJohn R. McDonnell, Don Waagen. 863-868 [doi]
• A method for the design of evolutionary multilayer neural networksSam-Kit Sin, Rui J. P. deFigueiredo. 869-874 [doi]
• Using evolutionary programing to create neural networks that are capable of playing tic-tac-toeDavid B. Fogel. 875-880 [doi]
• Evolving a sort: lessons in genetic programmingKenneth E. Kinnear Jr.. 881-888 [doi]
• Associative storage and retrieval of highly correlated natural pattern sets in diluted Hopfield networksKlaus-Robert Müller, Thomas Stiefvater, Herbert Janßen. 889-894 [doi]
• The hybrid Hopfield-clique memory with perfect storageJoerg Ueberla, Arun K. Jagota. 895-900 [doi]
• Multi-layer associative neural networks (MANN): storage capacity vs. noise-free recallHoon Kang. 901-907 [doi]
• Large scale simulations of a spin glass image associative memoryBruce E. Rosen, James M. Goodwin. 908-913 [doi]
• Partitions of unity improve neural function approximatorsHeinz Walter Werntges. 914-918 [doi]
• On the speed of training networks with correlated featuresRobert R. N. Bakker, Martin A. Kraaijveld, Robert P. W. Duin, Wouter F. Schmidt. 919-922 [doi]
• A neural network model based on differential-algebraic equations for nonlinear programmingMomiao Xiong, Jonathan Amold, Hubert J. Chen. 923-928 [doi]
• On the convergence of feedforward neural networks incoporating terminal attractorsColin R. Jones, Chi Ping Tsang. 929-935 [doi]
• An efficient algorithm for the binary classification of patterns using MLP-networksS. Fanelli, M. Di Martino, Marco Protasi. 936-943 [doi]
• On-line handwritten symbol recognition, using an ART based neural network hierarchyYannis A. Dimitriadis, Juan López Coronado, Celiano García Moreno, Jose-Manuel Cano-Izquierdo. 944-949 [doi]
• Power curves for pattern classification networksJanet M. Twomey, Alice E. Smith. 950-955 [doi]
• Towards an event-space self-configurable neural networkDavid K. Y. Chiu. 956-961 [doi]
• A serial complexity measure of neural networksMoshe Sipper. 962-966 [doi]
• Use of Kohonen's self-organizing network as a pre-quantizerS. A. Khaparde, Harish Gandhi. 967-971 [doi]
• An asynchronous neural network model for shortest path problemSonghe Zhao, Tharam S. Dillon. 972-976 [doi]
• Single minimum method for combinatorial optimization problems and an efficient algorithm of TSP problemDan Xu, Itsuo Kumazawa. 977-982 [doi]
• On the learning and convergence of the radial basis networksFu-Chuang Chen, Mao-Hsing Lin. 983-988 [doi]
• Polynomial and standard higher order neural networkChir-Ho Chang, Jin-Ling Lin, J. Y. Cheung. 989-994 [doi]
• Improved convergence for output scaling of a feedforward network with linear output nodesDonald I. Soloway. 995-997 [doi]
• Implementation of O(n) complexity max/min circuits for fuzzy and connectionist computingMohamad H. Hassoun, Ali M. Nabha. 998-1003 [doi]
• Robotic modeling and control using a fuzzy neural networkH. Y. Xu, G. Vukovich. 1004-1009 [doi]
• A neuro-fuzzy approach with pairwise comparisonsHidetomo Ichihashi, I. Burhan Türksen. 1010-1015 [doi]
• Fuzzified RBF network-based learning control: structure and self-constructionDerek A. Linkens, Junhong Nie. 1016-1021 [doi]
• A fuzzy neural network learning fuzzy control rules and membership functions by fuzzy error backpropagationDetlef Nauck, Rudolf Kruse. 1022-1027 [doi]
• Comparing learning performance of neural networks and fuzzy systemsChi Cheng Jou. 1028-1033 [doi]
• Inherent fault tolerance analysis for a class of multi-layer neural networks with weight deviationsXiaofan Yang, Tinghuai Chen. 1034-1039 [doi]
• Networks based on Kanerva's sparse distributed memory: results showing their strengths and limitations and a new algorithm to design the location matching layerRichard W. Prager. 1040-1045 [doi]
• Noise corrupted pattern retrieval capability for sparsely encoded associative memoryYo-Ping Huang, Donald Gustafson. 1046-1050 [doi]
• Sparse distributed memory for multivalued patternsJukka Vanhala, Juka Saarinen, Kimmo Kaski. 1051-1056 [doi]
• A new associative memory which inhibits a meaningless outputToshiaki Tanaka, Miki Yamada. 1057-1062 [doi]
• On the equivalence of two Hopfield-type networksTal Grossman, Arun Jagota. 1063-1068 [doi]
• Design of Hopfield content-addressable memoriesXinhua Zhuang, Yan Huang 0010. 1069-1074 [doi]
• Training a Hopfield memory with noisy examplesEnrique Carlos Segura. 1075-1080 [doi]
• Analog implementations of a binary relation inference network for minimum cost path problemsC. W. Tong, K. P. Lam. 1081-1085 [doi]
• Strictly digital neurocomputer based on a paradigm of constraint set programming for solving combinatorial optimization problemsTohru Nakagawa, Katsuhiko Murakami, Hajime Kitagawa. 1086-1091 [doi]
• Neural networks for solving the quadratic 0-1 programming problem under linear constraintsM. Aourid, B. Kaminska. 1092-1095 [doi]
• A real-time solution for the traveling salesman problem using a Boolean neural networkShirish Bhide, Nigel M. John, Mansur R. Kabuka. 1096-1103 [doi]
• Genetic algorithms and simulated annealing: a marriage proposalDan Adler. 1104-1109 [doi]
• Retaining diversity of genetic algorithms for multivariable optimization and neural network learningYoshiaki Ichikawa, Yoshikazu Ishii. 1110-1114 [doi]
• Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoringCharles C. Peck, Atam P. Dhawan, Claudia M. Meyer. 1115-1122 [doi]
• A dynamic routing control based on a genetic algorithmNorio Shimamoto, Atsushi Hiramatsu, Kimiyoshi Yamasaki. 1123-1128 [doi]
• A comparison of recurrent neural network learning algorithmsAntonette M. Logar, Edward M. Corwin, William J. B. Oldham. 1129-1134 [doi]
• Dynamics and stability of multilayered recurrent neural networksLiang Jin, Peter N. Nikiforuk, Madan M. Gupta. 1135-1140 [doi]
• Putting the simple recurrent network to the testJean-François Jodouin. 1141-1146 [doi]
• Things you haven't heard about the self-organizing mapTeuvo Kohonen. 1147-1156 [doi]
• A new acceleration technique for the backpropagation algorithmXiangui Yu, Nan K. Loh, William C. Miller. 1157-1161 [doi]
• Fuzzy function learning with covariance ellipsoidsJulie A. Dickerson, Bart Kosko. 1162-1167 [doi]
• Learning in the hypercubeVolnei A. Pedroni, Amnon Yariv. 1168-1171 [doi]
• Learning trajectories with a hierarchy of oscillatory modulesPierre Baldi, Nikzad Benny Toomarian. 1172-1176 [doi]
• Neural network construction using multi-threshold quadratic sigmoidal neuronsCheng-Chin Chiang, Hsin-Chia Fu. 1177-1182 [doi]
• The problem of learning long-term dependencies in recurrent networksYoshua Bengio, Paolo Frasconi, Patrice Y. Simard. 1183-1188 [doi]
• Practical considerations for Kalman filter training of recurrent neural networksGintaras V. Puskorius, Lee A. Feldkamp. 1189-1195 [doi]
• Constructive learning of recurrent neural networksDong Chen 0001, C. Lee Giles, Guo-Zheng Sun, H. H. Chen, Yee-Chun Lee, Mark W. Goudreau. 1196-1201 [doi]
• An unsupervised learning rule for vector normalization and gain controlMarc M. Van Hulle. 1202-1206 [doi]
• Is LVQ really good for classification?-an interesting alternativeWerner Pöchmüller, Manfred Glesner, H. Juergs. 1207-1212 [doi]
• Fast nonlinear dimension reductionNandakishore Kambhatla, Todd K. Leen. 1213-1218 [doi]
• Error potentials for self-organizationTom Heskes, Bert Kappen. 1219-1223 [doi]
• Intelligent FMS scheduling using modular neural networksLuis Rabelo, Yuehwern Yih, Albert T. Jones, George M. Witzgall. 1224-1229 [doi]
• Application of neural networks to fluorescent diagnostics of organic pollution in natural watersYuri V. Orlov, Igor Persiantsev, Sergey P. Rebrik. 1230-1235 [doi]
• Classification of chromosomes using a combination of neural networksPhil A. Errington, Jim Graham. 1236-1241 [doi]
• Two-bit weights are enough to solve vehicle license number recognition problemFerran Lisa, Jordi Carrabina, Conrado J. Pérez-Vicente, Narcís Avellana, Elena Valderrama. 1242-1246 [doi]
• An analog wavelet transform chipR. Timothy Edwards, Michael D. Godfrey. 1247-1251 [doi]
• Hardware implementation of an artificial neural networkNaleih M. Botros, M. Abdul-Aziz. 1252-1257 [doi]
• A neural network systems componentDean Mueller, Dan Hammerstrom. 1258-1264 [doi]
• Process models and network complexityEdward A. Rietman, Robert C. Frye, Earl R. Lory. 1265-1269 [doi]
• A multi-layer Kohonen's self-organizing feature map for range image segmentationJean Koh, Minsoo Suk, Suchendra M. Bhandarkar. 1270-1275 [doi]
• Segmentation of medical images through competitive learningAtam P. Dhawan, Louis Arata. 1277-1282 [doi]
• Neural network based object recognition in imagesDushan Z. Badal. 1283-1288 [doi]
• Hopfield-based adaptive state estimatorsRahmat Shoureshi, S. Reynold Chu. 1289-1294 [doi]
• Design of fault tolerant neurocontrollers using immunization techniqueD. U. Ekong, M. H. Adb-El-Barr, H. C. Wood. 1295-1300 [doi]
• An adaptive-topology neural architecture and algorithm for nonlinear system identificationGirish Govind, P. A. Ramamoorthy. 1301-1306 [doi]
• Self-tuning adaptive control of multi-input, multi-output nonlinear systems using multilayer recurrent neural networks with application to synchronous power generatorsSubramania I. Sudharsanan, I. Muhsin, Malur K. Sundareshan. 1307-1312 [doi]
• Neural nets, random design and reverse engineeringLawrence W. Stark. 1313-1320 [doi]
• The role of neural networks in the study of the posterior parietal cortexPietro Mazzoni, Richard A. Andersen. 1321-1326 [doi]
• Color opponency as the internal representation acquired by a three-layered neural network modelShiro Usui, Shigeki Nakauchi. 1327-1332 [doi]
• A relationship between neural networks and programmable logic arraysVictor Eliashberg. 1333-1337 [doi]
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• BAYESNET: Bayesian classification network based on biased random competition using Gaussian kernelsSukhan Lee 0001, Shunichi Shimoji. 1354-1359 [doi]
• How lateral interaction develops in a self-organizing feature mapJoseph Sirosh, Risto Miikkulainen. 1360-1365 [doi]
• Quantization effects of Hebbian-type associative memoriesPau-Choo Chung, Yi-Nung Chung, Ching-Tsorng Tsai. 1366-1370 [doi]
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• CMAC learning is governed by a single parameterYiu-Fai Wong. 1439-1443 [doi]
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• Unsupervised learning for multivariate probability density estimation: radial basis and projection pursuitJenq-Neng Hwang, Shyh-Rong Lay, Alan Lippman. 1486-1491 [doi]
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