Рефераты. Функциональные модели универсального нейрокомпьютера

296.        Gorban A.N., Mirkes Ye.M. and Wunsch D.C. II High order ortogonal tensor networks: Information capacity and reliability // ICNN97 (The 1997 IEEE International Conference on Neural Networks), Houston, 1997.- P.1311-1314.

297.        Gorban A.N., Mirkes Ye.M. Functional Components of Neurocomputer // Математика, компьютер, образование: Тр. третьей международной конференции.- М., 1996.- С.352-359.

298.        Gorban A.N., Mirkes Ye.M. Functional components of neurocomputer // Mathematics, computer, education: Abstracts of 3-d International conference.- Dubna, 1996.- p. 160.

299.        Gorban A.N., Novokhodko A.Yu.. Neural Networks In Transposed Regression Problem // Proc. of the World Congress on Neural Networks, Sept.15-18, 1996.- San Diego, CA, 1996/- P.515-522.

300.        Gorban A.N., Rossiev D.A., Butakova E.V., Gilev S.E., Golovenkin S.E., Dogadin S.A., Dorrer M.G., Kochenov D.A., Kopytov A.G., Maslennikova E.V., Matyushin G.V., Mirkes Ye.M., Nazarov B.V., Nozdrachev K.G., Savchenko A.A., Smirnova S.V., Shulman V.A., Zenkin V.I. Medical, psychological and physiological applications of MultiNeuron neural simulator. Neuroinformatics and Neurocomputers // Proceedings of the second RNNS-IEEE Simposium.- Rostov-na-Donu, 1995.- P.7-14.

301.        Gorban A.N., Rossiev D.A., Gilev S.E. et al. “NeuroComp” group: neural-networks software and its application.- Krasnoyarsk, 1995.- 38 p. (Preprint / Russian Academy of Sciences, Krasnoyarsk Computing Center; № 8)

302.        Gorban A.N., Rossiev D.A., Gilev S.E., Dorrer M.A., Kochenov D.A., Mirkes Ye.M., Golovenkin S.E., Dogadin S.A., Nozdrachev K.G., Matyushin G.V., Shulman V.A., Savchenko A.A. Medical and physiological applications of MultiNeuron neural simulator // Proceedings of World Congress on Neural Networks.- Washington DC, 1995.- P.170-175.

303.        Gorban A.N., Waxman C. How many neurons are sufficient to elect the U.S.A. President?// AMSE Transaction, Scientific Siberian.- 1993.- V. 6.- P.168-188.

304.        Gorban A.N., Waxman C. How many Neurons are Sufficient to Elect the U.S.A. President? TWO! (Siberian neurocomputer forecasts results of U.S.A. Presidential elections).- Krasnoyarsk, 1992.- 29 p. (Preprint / Russian Academy of Sciences Siberian Branch, Institute of Biophysics; № 191 Б).

305.        Gorban A.N., Waxman C. Neural networks for political forecast // Proceedings of the WCNN'95.- Washington DC, 1995.- P.179-184.

306.        Gordienko P. Construction of efficient neural networks // Proceedings of the International Conference on Neural Information Processing (Oct. 17-20, 1994, Seoul, Korea).- V.1.- P.366-371.

307.        Gordienko P. How to obtain a maximum of skills with minimum numbers of connections // AMSE Transaction, Scientific Siberian, 1993.- V.6.- P.204-208.

308.        Gross G.W., Boone J.M., Greco-Hunt V. et al. Neural networks in radiologic diagnosis. II. Interpretation of neonatal chest radiographs // Invest. Radiol.- 1990.- V.25, № 9.- P.1017-1023.

309.        Grossberg S. Nonlinear Neural Networks: Principles, Mechanism and Architectures// Neural Networks.- 1988.- V.1, № 1.- P.17-62.

310.        Guo Z., Durand L.G., Lee H.C. et al. Artificial neural networks in computer-assisted classification of heart sounds in patients with porcine bioprosthetic valves // Med. Biol. Eng. Comput.- 1994.- V.32, № 3.- P.311-316.

311.        Hecht-Nielsen R. Neurocomputing.- Addison-Wesley, 1990.- 458 p.

312.        Hecht-Nielsen R. Neurocomputing: Picking the Human Brain / IEEE Spectrum, 1988.- March.- P.36-41.

313.        Heht-Nielsen R. Theory of the backpropagation neural network // Neural Networks for Human and Mashine Perception / By ed. H.Wechsler.- Boston, MA: Academic Press, 1992.- V.2.- P.65-93.

314.        Hod H., Lew A.S., Keltai M. et al. Early atrial fibrillation during evolving myocardial infarction: a consequence of impaired left atrial perfusion // Circulation, 1987.- V.75, № 1.- P.146-150.

315.        Hoher M., Kestler H.A., Palm G. et al. Neural network based QRS classification of the signal averaged electrocardiogram // Eur. Heart J.- 1994.- V.15.- Abstr. Supplement XII-th World Congress Cardiology (734).- P.114.

316.        Hopfield J.J. Neural Networks and physical systems with emergent collective computational abilities // Proc. Nat. Sci. USA, 1982.- V.79.- P.2554-2558.

317.        Hornik K., Stinchcombe M., White H. Multilayer Feedforward Networks are Universal Approximators // Neural Networks.- 1989.- V.2.- P.359-366.

318.        Jeffries C. Code recognition with neural network dynamical systems // SIAM Rev.- 1990.- V.32, № 4.- P.636-651.

319.        Kalman R.E. A theory for the identification of linear relations // Frontiers Pure and Appl. Math.: Collect. Pap. Dedicat. Jacques-Louis Lions Occas. His 60th Birthday: Sci. Meet., Paris, 6-10 June, 1988.- Amsterdam, 1991.- P.117-132.

320.        Keller J.M., Yager R.R., Tahani H. Neural network implementation of fuzzy logic // Fuzzy Sets and Syst.- 1992.- V.45, № 1.- P.1-12.

321.        Kirdin A.N., Rossiev D.A., Dorrer M.G. Neural Networks Simulator for Medical, Physiological and Psychological Applications // Математика, компьютер, образование: Тр. третьей международной конференции.- М., 1996.- С.360-367.

322.        Kirdin A.N., Rossiev D.A.. Neural-networks simulator for medical and physiological applications // Mathematics, computer, education: Abstracts of 3-d International conference.- Dubna, 1996.- P.162.

323.        Kochenov D.A., Rossiev D.A. Approximations of functions of C[A,B] class by neural-net predictors (architectures and results)// AMSE Transaction, Scientific Siberian, 1993.- V.6.- P.189-203.

324.        Kock, G., Serbedzija, N.B. Artificial Neural Networks: From Compact Descriptions to C++ // ICANN'94: Proc. of the Int. Conf. on Artificial Neural Networks, 1994.- P.548.

325.        Kock, G., Serbedzija, N.B. Object-Oriented and Functional Concepts in Artificial Neural Network Modeling // Proc. Int. Joint Conf. on Neural Networks.- Nagoya (Japan), 1993.- Р.483.

326.        Kock, G., Serbedzija, N.B.. Specification of Artificial Neural Networks based on the modified AXON Model // Proc. World Congress on Neural Networks.- Portland, 1993.- V. I.- P.433-436.

327.        Koopmans T. Serial correlation and quadratic forms in normal variates // Ann. Math. Statist.- 1942.- V. 13.- P.14-33.

328.        Korver M., Lucas P.J. Converting a rule-based expert system into a belief network // Med. Inf. Lond.- 1993.- V.18, № 3.- P.219-241.

329.        Kosko B. Bidirectional Associative Memories // IEEE Transactions on Systems, Man, and Cybernetics.- 1988.- V. SMC-18.- P.49-60.

330.        Le Cun Y., Denker J.S., Solla S.A. Optimal Brain Damage // Advances in Neural Information Processing Systems II (Denver 1989).- San Mateo, 1990.- P.598-605

331.        Lee H.-L., Suzuki S., Adachi Y. et al. Fuzzy Theory in Traditional Chinese Pulse Diagnosis // Proceedings of 1993 International Joint Conference on Neural Networks, Nagoya, Japan, October 25-29.- Nagoya, 1993.- V.1.- P.774-777.

332.        Levine D.S., Parks R.W., Prueitt P.S. Methodological and theoretical issues in neural network models of frontal cognitive functions // Int. J. Neurosci.- 1993.- V.72, № 3-4.- P.209-233.

333.        Lichtman A.J., Keilis-Borok V.I., Pattern Recognition as Applied to Presidential Elections in U.S.A., 1860-1980; Role of Integral Social, Economic and Political Traits, Contribution No. 3760. 1981, Division of Geological and Planetary Sciences, California Institute of Technology.

334.        Maclin P.S., Dempsey J. Using an artificial neural network to diagnose hepatic masses // J. Med. Syst.- 1992.- V.16, № 5.- P.215-225.

335.        Macukow B. Robot control with neural networks // Artif. Intell. and Inf.-Contr. Syst. Rob.-89: Proc. 5th Int. Conf., Strbske Pleso, 6-10 Nov., 1989.- Amsterdam, 1989.- P.373-376.

336.        Mirkes E.M., Svitin A.P. The usage of adaptive neural networks for catalytic activity predictions // CHISA - 10th Int. Congr. of chem. eng., chem. equipment design and automation. Praha, 1990. Prepr. B3.80 [1418]. 7 p.

337.        Modai I., Stoler M., Inbar-Saban N. et al. Clinical decisions for psychiatric inpatients and their evaluation by a trained neural network // Methods Inf. Med.- 1993.- V.32, № 5.- P.396-399.

338.        Modha D.S., Heht-Nielsen R. Multilayer Functionals // Mathematical Approaches to Neural Networks / By ed. J.G.Taylor.- Elsevier, 1993.- P.235-260.

339.        Nakajima H., Anbe J., Egoh Y. et al. Evaluation of neural network rate regulation system in dual activity sensor rate adaptive pacer // European Journal of Cardiac Pacing and Electrophysiology: Abstracts of 9th International Congress, Nice Acropolis - French, Rivera, June 15-18, (228), 1994.- Rivera, 1994.- P.54.

340.        Narendra K.S., Amnasway A.M. A stable Adaptive Systems.- Prentice-Hall, 1988.- 350 p.

341.        Neural Computers / Ed. by R. Eckmiller, Ch. Malsburg.- Springer, 1989.- 556 p.

342.        Okamoto Y., Nakano H., Yoshikawa M. et al. Study on decision support system for the interpretation of laboratory data by an artificial neural network // Rinsho. Byori.- 1994.- V.42, № 2.- P.195-199.

343.        Pedrycz W. Neurocomputations in relational systems // IEEE Trans. Pattern Anal. and Mach. Intell.- 1991.- V.13, № 3.- P.289-297.

344.        Pham D.T., Liu X. Statespace identification of dynamic systems using neural networks // Eng. Appl. Artif. Intell.- 1990.- V.3, № 3.- P.198-203.

345.        Pineda F.J. Recurrent bakpropagation and the dynamical approach to adaptive neural computation // Neural Comput.- 1989.- V.1.- P.161-172.

346.        Poli R., Cagnoni S., Livi R. et al. A Neural Network Expert System for Diagnosing and Treating Hypertension // Computer.- 1991.- № 3.- P.64-71.

347.        Prechelt L. Comparing Adaptive and Non-Adaptive Connection Pruning With Pure Early Stopping // Progress in Neural Information Processing (Hong Kong, September 24-27, 1996).- Springer, 1996.- V.1.- P.46-52.

348.        Real Brains, Artificial Minds / Ed. by J.L. Casti, A. Karlqvist.- Norton-Holland, 1987.- 226 p.

349.        Reinbnerger G., Weiss G., Werner-Felmayer G. et al. Neural networks as a tool for utilizing laboratory information: comparison with linear discriminant analysis and with classification and regression trees // Proc. Natl. Acad. Sci., USA.- 1991.- V.88, № 24.- P.11426-11430.

350.        Rinast E., Linder R., Weiss H.D. Neural network approach for computer-assisted interpretation of ultrasound images of the gallbladder // Eur. J. Radiol.- 1993.- V.17, № 3.- P.175-178.

351.        Rossiev D.A., Golovenkin S.E., Shulman V.A., Matyushin G.V. Forecasting of myocardial infarction complications with the help of neural networks // Proceedings of the WCNN'95 (World Congress on Neural Networks'95, Washington DC, July 1995).- Washington DC, 1995.- P.185-188.

352.        Rossiev D.A., Golovenkin S.E., Shulman V.A., Matyushin G.V. Neural networks for forecasting of myocardial infarction complications // Proceedings of the Second IEEE RNNS International Symposium on Neuroinformatics and Neurocomputers, September 20-23, 1995.- Rostov-on-Don, 1995.- P.292-298.

353.        Rossiev D.A., Golovenkin S.E., Shulman V.A., Matyushin G.V. The employment of neural networks to model implantation of pacemaker in patients with arrhythmias and heart blocks // Modelling, Measurument & Control, C.- 1995.- V. 48, № 2.- P.39-46.

354.        Rossiev D.A., Golovenkin S.E., Shulman V.A., Matyushin G.V. The employment of neural networks to model implantation of pacemaker in patients with arrhythmias and heart blocks // Proceedings of International Conference on Neural Information Processing, Oct. 17-20, 1994, Seoul, 1994.- V.1.- P.537-542.

355.        Rossiev D.A., Savchenko A.A., Borisov A.G., Kochenov D.A. The employment of neural-network classifier for diagnostics of different phases of immunodeficiency // Modelling, Measurement & Control.- 1994.- V.42, № 2.- P.55-63.

356.        Rozenbojm J., Palladino E., Azevedo A.C. An expert clinical diagnosis system for the support of the primary consultation // Salud. Publica Mex.- 1993.- V.35, № 3.- P.321-325.

357.        Rumelhart D.E., Hinton G.E., Williams R.J. Learning internal representations by error propagation // Parallel Distributed Processing: Exploration in the Microstructure of Cognition / By ed. D.E.Rumelhart, J.L.McClelland.- V.1.- Cambridge, 1986.- P.318-362.

358.        Rummelhart D.E., Hinton G.E., Williams R.J. Learning representations by back-propagating errors // Nature.- 1986.- V.323.- P.533-536.

359.        Saaf L. A., Morris G. M. Filter synthesis using neural networks // [Pap.] Opt. Pattern Recogn. II: Proc. Meet., Paris, 26-27 Apr., 1989.- Proc. Soc. Photo-Opt. Instrum. Eng.- 1989.- V.1134.- P.12-16.

360.        Sandberg I.W. Approximation for Nonlinear Functionals // IEEE Transactions on Circuits and Systems - 1: Fundamental Theory and Applications, Jan.- 1992.- V.39, № 1.- P.65 67.

361.        Savchenko A.A., Zakharova L.B., Rossiev D.A. The employment of neural networks for investigation & diagnostics of Viliuisk encephalomyelitis // Modelling, Measurement & Control, C.- 1995.- V.48, № 4.- P.1-15.

362.        Senashova M.Yu., Gorban A.N. and. Wunsch D.C. II. Back-propagation of accuracy // ICNN97 (The 1997 IEEE International Conference on Neural Networks).- Houston, 1997.- P.1998-2001.

363.        Senna A.L., Junior W.M., Carvallo M.L.B., Siqueira A.M. Neural Networks in Biological Taxonomy // Proceedings of 1993 International Joint Conference on Neural Networks, Nagoya, Japan, October 25-29, 1993.- Nagoya, 1993.- V.1.- P.33-36.

364.        Stefanuk V.L. Expert systems and its applications // The lectures of Union's workshop on the main problems of artificial intillegence and intellectual systems. Part 2.- Minsk, 1990.- P.36-55.

365.        Sussman H.J. Uniqueness of the weigts for minimal feedforward nets wits a given input - output map // Neural Networks.- 1992.- № 5.- P.589-593.

366.        Sweeney J.W.P., Musavi M.T., Guidi J.N. Probabilistic Neural Network as Chromosome Classifier // Proceedings of 1993 International Joint Conference on Neural Networks, Nagoya, Japan, October 25-29, 1993.- Nagoya, 1993.-V.1.- P.935-938.

367.        Tabatabai A., Troudet T. P. A neural net based architecture for the segmentation of mixed gray-level and binary pictures // IEEE Trans. Circuits and Syst.- 1991.- V.31-38, № 1.- P.66-77.

368.        Tao K.M., Morf M. A lattice filter type of neuron model for faster nonlinear processing // 23th Asilomar Conf. Signals, Syst. and Comput., Pasific Grove, Calif. Oct. 30-Nov. 1, 1989: Conf. Rec. V. 1.- San Jose (Calif.), 1989.- P.123-127.

369.        The Adaptive Brain / By ed. S. Grossberg.- North-Holland, 1987.- V.1. Cognition, Learning, Reforcement, and Rhythm. 498 p.; V.2. Vision, Speech, Language, and Motor Control. 514 p.

370.        The Computer and the Brain. Perspectives of Human and Artificial Intelligence / By ed. J.R. Brinc, C.R. Haden, C. Burava.- North-Holland, 1989.- 300 p.

371.        Vakhrushev S.G., Rossiev D.A., Burenkov G.I., Toropova L.A. Neural network forecasting of optimal parameters of laserotherapy in patients after tonsillectomy // Proceedings of World Congress on Neural Networks.- 1995.- P.176-178.

372.        Van Leeuwen J.L. Neural network simulations of the nervous system // Eur. J. Morphol.- 1990.- V.28, № 2-4.- P.139-147.

373.        Varela F.J., Coutinho A., Dupire B. et al. Cognitive networks: immune, neural and otherwise // Teoretical immunology / By ed.  Perelson A.- Addison Wesley, 1988.- Part 2.- P.359-375.

374.        Waxman C. Neurocomputers in the human sciences: program: predictions of US presidential elections// Modelling, Measurement & Control, D.- 1992.- V.5, № 1.- P.41-53

375.        Weckert J. How expert can expert systems really be? // Libr. and Expert Syst.: Proc. Conf. and Workshop [Centre Inf. Stud.], Riverina, July, 1990.- London, 1991.- PP. 99-114.

376.        Wiedermann J. On the computation efficiency of symmetric neural networks // Theor. Comput. Sci.- 1991.- V.80, № 2.- P.337-345.

377.        Wong K.Y.M., Kahn P.E., Sherrington D. A neural network model of working memory exhibiting primacy and recency // J. Phys. A.- 1991.- V.24, № 5.- P.1119-1133.

378.        Yang T.-F., Devine B., Macfarlane P.W. Combination of artificial neural networks and deterministic logic in the electrocardiogram diagnosis of inferior myocardial infarction // Eur. Heart J.: Abstr. Supplement XII-th World Congress Cardiology (2408).- 1994.- V.15.- P.449.



Страницы: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76



2012 © Все права защищены
При использовании материалов активная ссылка на источник обязательна.