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Gesamtliteraturliste Neuroscience

 


Günter Bachelier, Dr. phil.

 

 


A B C D E F G H I J K L M N O P Q R S T U V W X Y Z


 

  Interne Referenz Autor: Titel. Jahr

A

   
  [AbuMostafa_NNFin95] Abu-Mostafa, Y; Refenes, A-P; Moody, J.; Weigend, A.: Neural Networks in Financial Engineering. Proceedings of the Third Int. Conf. on Neural Networks in the Capital Markets 1995. World Scientific, 1996.
  [AbuMostafa_NNFin96] Abu-Mostafa, Y; Refenes, A-P; Weigend, A.: Decision Technologies for Financial Engineering. Proceedings of the Fourth Int. Conf. on Neural Networks in the Capital Markets 1996. World Scientific, 1997.
  [Abu_LerningHints] Abu-Mostafa, Y.: Learning from hints. In: Journal of Complexity. 10, 165-178, 1994.
  [Adelman_EncyNeuroScience] Adelman, George: Encyclopedia of Neuroscience. Birkhäuser, 1987.
  [Aizenberg_MultiValue] Aizenberg, J.N.; Aizenberg, N.N.; Vonderwalle, J.: Multi-Valued and Universal Binary Neurons. Kluwer, 2000.
  [Albrecht_ANNGA93] Albrecht, R.F.; Reeves, C.R.; Steele, N.C.: Artificial Neural Networks and Genetic Algorithms. Proceedings, Insbruck, 1993. Springer, 1993.
**  

Amari, S.; Murara, N.; MŸller, K.-R.; Finke, M.; Yang, H.: Asymptotic Statistical Theory of Overtraining and Cross-Validation. Dep. of Mathematical Engineering, University of Tokyo, Technical Report METR 95-06, September 1996. { 108, 428} (ftp://archive.cis.ohio-state.edu/pub/neuroprose/amari.overtraining.ps.Z).

**   Amari, S.; Murara, N.; MŸller, K.-R.; Finke, M.; Yang, H.: Statistical Theory of Overtraining - Is Cross-Validation Effective? In: Touretzky et al. (1996[336]), NIPS 8, S. 176-182. { 108, 428} (http://www.first.gmd.de/persons/Mueller.Klaus-Robert/nips_crossval.ps.Z).
  [Arbib_BrainNN] Arbib, Michael A.: The Handbook of Brain Theory and Neural Networks. MIT Press, 1995.
  [Armstrong_AdapBiTree79] Armstrong, W.W.; Gecsei, J.: Adaption Algorithms for Binary Tree Networks. In: IEEE Transactions on Systems, Man and Cybernetics Vol. SMC-9 Nr. 5 May 1979, S. 276-285.
  [Armstrong_ANN_Vehicle] Armstrong, W.W.; Thomas, M.M.: Control of a Vehicle active suspension system model using Adaptive Logic Networks. Report, 1994.
  [Atree3_DevelopSy] Atree 3 ALN Development System
  [Austin_RAM-NN] Austin, James (ed): RAM Based Neural Networks. World Scientific, 1998.

B

 
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**   Bartell, Brian T.: Optimizing Ranking Functions: A Connectionist Approach to Adaptive Information Retrieval. Ph.D. thesis, Department of Computer Science and Engineering, University of California, San Diego, 1994. (http://www.bartell.com/bbartell/thesis_1sp.ps).
**   Baum, Eric B.: Neural net algorithms that learn in polynomial time from examples and queries. In: IEEE Transactions on Neural Networks 2(1), 1991, S. 5 - 19.
**   Baum, Eric B.; Lang, K. J.: Constructing hidden units using examples and queries. In: Lippmann et al. (1991[201]), NIPS 3, 1991, S. 904 - 910. (http://nips.djvuzone.org/djvu/nips03/0904.djvu).
  [Basar_ChaosBrain] Basar, Erol (ed): Chaos in Brain Functions. Springer, 1990.
  [Basri_RecogProto] Basri, Ronen: Recognition by Prototypes. MIT AI Memo 1391, Dec. 1992.
  [Beale_NNPatternRec] Beale, R.; Finlay, J.: Neural Networks and Pattern Recognition in Human-Computer Interaction. Ellis Horwood, 1992.
  [Bertsekas_NeuDyProgramming] Bertsekas, D.P.; Tsitsiklis, J.N.: Neuro-Dynamic Programming. Athena Scientific, 1996.
**   Beyer, Uwe; Smieja, Frank: Data Exploration with Reflective Adaptive Models. GMD, St. Augustin, 1994. (ftp://borneo.gmd.de/pub/as/janus/ref94_1.ps).
  [Bothe-Neurobionik] Bothe, H.-W.; Engel, M. Neurobionik. Umschau, 19xx.
  [BoxSOM-Dis02] Galliat, T.: Adaptive Multilevel Cluster Analysis by Self-Organizing Box Maps. Dissertation Fachbereich Mathematik und Informatik, FU Berlin, 2002
  [Bradshaw_LateralAsym] Bradshow, J.L.; Rogers L.J.: The Evolution of Lateral Asymmetries, Language, Tool use and Intellect. Acad. Press, 1993.
  [Brause_NN91] Brause, R.: Neuronale Netze. Teuber, 1991.
  [Bruske_DCS] Bruske, J.; Sommer, G.: Dynamic Cell Structures: Radial Basis Function Networks with Perfect Topology Preservation. Bericht 9403 Institut Informatik und Praktische Mathematik, Uni Kiel, 1994.
  [Buckley_Fuzzy+IntervalNN] Buckley, J.J.; Feuring, T.: Fuzzy and Neural: Interactions and Applications. Physica Verlag, 1999.

C

 
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  [Calvin_CerebralCode] Calvin, W.: The Cerebral Code. Bradford Book, 1996.
  [Castillo_FunctionalNN] Castillo, E.; Cobo, A.; Gutierrez, J.M.; Pruneda, R.E.: Functional Networks with Applications. Kluwer, 1999.
  [Chappell_TempoKoho] Chappell, G.J.; Taylor, J.G.: The Temporal Kohonen Map. In: Neural Networks Vol. 6, S. 441-445, 1993.
  [Churchland_NeuroInfo] Churchland, P.; Sejnowski, T.J.: Grundlagen zur Neuroinformatik und Neurobiologie. Vieweg, 1997.
  [Cichocki_NNSigProc] Cichocki, A. Unbehagen, R.: Neural Networks for Optimization and Signal Processing. Wiley & Sons, 1993.
**  

Cohn, David A.; Atlas, L.: Ladner, R.: Training connectionist networks with queries and selective sampling. In: Touretzky (1990[335]), NIPS 2, S. 566 - 573. (http://nips.djvuzone.org/djvu/nips02/0566.djvu).

**  

Cohn, David A.: Queries and exploration using optimal experiment design. In: Cowan et al. (1994[80]), NIPS 6, S. 679 - 686. (http://nips.djvuzone.org/djvu/nips06/0679.djvu).

**  

Cohn, David A.; Atlas, Les; Ladner, Richard: Improving generalization with active learning. In: Machine Learning 15(2), 1994, S. 201 - 221.

**  

Cohn, David A.: Minimizing Statistical Bias with Queries. MIT AI Memo Nr. 1552, 1995. (http://www.ai.mit.edu/people/cohn/psyche/bias.ps.Z).

**   Cohn, David A.; Ghahramani, Zoubin; Jordan, Michael I.: Active Learning with Statistical Models. In: Tesauro et al. (1995[331]), NIPS 7, S. 705 - 712.(http://nips.djvuzone.org/djvu/nips07/0705.djvu).
  [Corrochano_GeoComp] Corrochano, E.B.: Geometric Computing for Perception Action Systems. Springer, 2001.
**   Cowan, Jack D.; Tesauro, Gerald; Alspector, Joshua (eds.): Advances in Neural Information Processing Systems 6, NIPS 6. San Mateo, CA, 1994.
  [ct_88_10_S84] Benz, H.J.: Ein Gehirn für den PC. In: ct 10/1988, S. 84-92.
  [ct_90_07_S80] Kötter, R.; Benz, H.J.: Asspziativspeicher auf Unix Systemen. In: ct 07/990, S. 80-83.
  [Cunningham_temporalNN] Cunningham, R.K.; Waxman, A.M.: Diffusion-Enhancement Bilayer. In: Neural Networks Vol. 7 Nr. 6/7, S. 895 -924, 1994.
**   Cunningham, Sally Jo; Holmes, Geoffrey; Littin, Jamie; Beale, Russell; Witten, Ian H.: Applying connectionist models to information retrieval. Department of Computer Science, The University of Waikato Hamilton, New Zealand, 1997. (http://www.cs.waikato.ac.nz/~ml/publications/1997/SJC-GH-JL-RB-IHW97.pdf).

D

 
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  [Deco_InfTheoNN] Deco, G.; Obradovic, D.: An Informationtheoretic approach to Neural Computing. Springer, 1996.
  [Denz_OpticalNN] Denz, Cornelia: Optical Neural Networks. Vieweg, 1998.
  [Der-SOM_93] Der, R.; Villmann, Th.: Dynamics of Self-organized Feature Mapping. In: ____, 1993.
  [Der-SOM_94] Der, R.; Herrmann, M.: Critical phenomena in self-organizing feature maps: Ginsburg-Landau approach. In: Physical Review E, Vol. 49, Nr. 6, S. 5840 - 5848, 1994.
  [Diamantaras_PrincComp] Diamantaras, K.I.; Kung, S.Y.: Principal component Neural Networks. Wiley & Sons, 1996.
  [Dorffner_Konnek_91] Dorfner, G.: Konnektionismus. Teubner, 1991.
  [Dorffner_NNStandard] Dorfner, G.; Wiklicky, H.; Prem, E.: Formal Neural Network Specification and its Implications on Standardization. TR-92-24, Öster. Forschungsinstitut für Artificial Intelligence, 1993.
**   Drucker, H.; Cortes, C.: Boosting Decision Trees. In: Touretzky et al. (1996[336]), NIPS 8, S. 479 Ð 485. (http://nips.djvuzone.org/djvu/nips08/0479.djvu).

E

 
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  [Eckmiller_NNCom88] Eckmiller, R.; Malsburg, Ch. v.d. (eds.): Neural Computers. Springer, 1989.
  [Eibelsfeld_BioMensch] Eibel-Eibelsfeld, I.: Die Biologie des menschlichen Verhaltens. Seehamer Verl., 1997.

F

 
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  [Freeman_NNMathe] Freeman, J.A.: Simulationg Neural Networks with Mathematica. Add.-Wesley, 1994.
  [Fršscher_Neurologie] Fröscher,W. (Hersg.): Lehrbuch Neurologie. Bechtermünz, 2002.
  [Furuhashi_FuzLNNGA94] Furuhashi, T. (ed.): Advances in Fuzzy Logik, Neural Networks and Genetic Algorithms. Springer, 1995.
  [FuzzyKoho_IEEE92] Bezdek, J,C.; Tsao, E.C.-K.; Pal, N.R.: Fuzzy Kohonen Clustering Networks. In: IEEE ______, 1992
  [FuzzyKoho_IJCNN93] Ishibuchi, H; Nozaki, K.; Weber, R.: Approximate Pattern Classifikation with Fuzzy Boundary. In: Proc. 1993 Int. Join Conf Neural Networks, S. 693 - 696, 1993.
  [FuzzySOM_Dortm94] Iukarainen, T.; Kärpänoja, E.: Gas Recognition using Fuzzy Self-Organizing Maps. Dortmund Fuzzy S. 144-158, 1994.
**  

Fritzke, Bernd: Wachsende Zellstrukturen - Ein selbstorganisierendes Neuronales Netzwerkmodell. Arbeitsberichte des Instituts fŸr mathematische Maschinen und Datenverarbeitung der Friedrich Alexander UniversitŠt Erlangen-NŸrnberg, Dissertation, 1992. (http://pikas.inf.tu-dresden.de/~fritzke/papers/thesis.ps.gz).

**  

Fritzke, Bernd: Superviced learning with growing cell structures. In: Cowan et al. (1994[80]), S. 255 - 262, 1994. (http://pikas.inf.tu-dresden.de/~fritzke/papers/fritzke.nips93.ps.gz).

**  

Fritzke, Bernd: A Growing Neural Gas Network Learns topologies. In: Tesauro et al. (1995[331]), NIPS 7, S. 625 - 632. (ftp://ftp.neuroinformatik.ruhr-uni-bochum.de/pub/manuscripts/articles/fritzke.nips94.ps.gz).

**  

Fritzke, Bernd: Growing Self-organizing Networks - Why? In: Verleysen (1996[349]): S. 61 - 72. (http://pikas.inf.tu-dresden.de/~fritzke/ftppapers/fritzke.esann96.ps.gz).

**   Fritzke, Bernd: Vektorbasierte Neuronale Netze. Habilitation, Shaker Verlag, 1998. { 59, 73} (http://pikas.inf.tu-dresden.de/~fritzke/papers/habil.ps.gz).

G

 
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**   Geman, S.; Bienenstock, E. Doursat, R.: Neural Networks and the Bias/Variance Dilemma. In: Neural Computation, 4, S. 1 -58, 1992.
  [Gersho_VecQuanti] Gersho, A.; Gray, R.M.: Vektor Quantifization and Signal Compression. Kluwer, 1992.
  [GMD-Studien_242(HeKonn94)] GMD Studie 242 (HeKonn94)
  [GMD2/95_DErh_Paa§] Kindermann, J.; Paaß G.: Konstruktive Datenerhebung mit reflektiven neuronalen Netzen. In: GMD Spiegel 2/1995.
  [GMD_857_NN] GMD Studie 857
  [Gšbel_VisuAufmNN] Goebel, R.: Visuelle Aufmerksamkeit, perzeptive Organisation und invariante Objekterkennung. Dissertation, Naturwisenschaftl. Fakultät der Univ. Braunschweig, 1996.
  [Gšppert-Dis] Göppert, J.: Die topologische interpolierende selbstorganisierende Karte in der Funktionsapproximation. Dissertation, Univ. Tübingen, Shaker Verl. 1997.
  [Gšppert_ISOM] Göppert, J.; Rosenstiel, W.: Dynamic Extentions of selforganizing maps. In: Proc. ICANN 94, Sorrento, Springer, 1994.
  [Gurney_RAMNets92a] Gurey, K.N.: Training Recurrent Nets of hardware realisable Sigma-Pi Units. In: Jour. Neural Systems, Vol. 3, S. 31.42, 1992.
  [Gurney_RAMNets92b] Gurey, K.N.: Weighted Nodes and RAM Nets: A Unified Approach. In: Journal of Intel. Systens, S. 155-185, 1992.

H

 
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  [Hafner_NNAutom] Hafner, S.: Neuronale Netze in der Automaisierungstechnik. Oldenburgverlag. 1994.
  [Haken_GehirnVerhalten] Haken, H.; Haken-Krell, M.: Gehirn und Verhalten. DVA, 1997
  [HŠnggi_CellularNN] Hänggi, M.; Moschytz, G.S. Cellular Neural Networks. Kluwer, 2000.
**   Hanson, Steve J.; Cowan, Jack D.; Giles, C. Lee (eds.): Advances in Neural Information Processing Systems 5, NIPS 5. San Mateo, Calif., 1993.
  [HechtNielson_NNComp] Hecht-Nielsen, R.: Neurocomputing. Addison-Wesley. 1990.
  [Helm_Symb+KonnekWis] Helm, G.: Symbolische und konnektionistische Modelle der menschlischen Informationsverarbeitung. Springer, 1991.
  [Hinton_UnsupLearning] Hinton, G.; Sejnowski, T.J.: Unsuperviced Learning. MIT Press, 1999.
  [Holden_CrossVPAC] Holden, S.B.: Cross-Validation and PAC Learning. TR RN/99/64. 1994.
  [Huchinson_RBFFinance] Hutchinson, J.M.: A Radial Basis Function Approach to Financial Time Series Analysis. Dissertation, MIT, 1994.
  [Hulle_Topographic] Hulle, M.M. Van: Faithful Representations and Topographic Maps. Wiley & Son, 2000.

I

 
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  [ICANN96] Marlsburg, C.v.d.; Seelen W.v.; Vorbrüggen, J.C.; Sendhoff, B. (eds.); Artificial Neural networks, ICANN96, Bochum, 1996, Springer, 1996.
# [ICANN_92]  
  [IWANN99] Mira, J.; Sanchez-Andres, J.V. (eds.): Engineering Applications of Bio-Inspired Artificial Neural Networks. IWANN99, Vol. 2, Springer 1999.
  [iX_2_91_52-58] Kötter. R.; Bentz, H.J.: "Binäre Assoziations Matrix". In: iX, 2/1991, S.52-58.

J

 
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  [JNN_V7_N8_S1229] Jockusch, S.; Ritter, H.: Self-organizing Maps: Local Competition and Evolutionary Optimization. In: Neural Networks, Vol. 7, Nr. 8, S. 1229-1239, 1994.
  [Jones_DimReduc] Jones, M.J.: Using Recurrent Networks for Dimensionality Reduction. Master of Science, Dep. Elec. Engeneering and Computer Science, MIT, 1992.

K

 
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  [Kappen_3SNN95] Kappen, B.; Gielen, S.: Neural Networks: Artificial Intelligence and Industrial Applications. 3 SNN Symposium, Nijmegen, 1995, Springer, 1995.
# [Kargupta_TempSeq] Kargupta, H.; Ray, S.R.: Temporal Sequence Processing Based on the Biological Reaction-Diffusion Process. In: IEEE _____, 1994.
  [Kelso_DyPatterns] Kelso, J.A.S.: Dynamic Patterns. MIT Press, 1995.
  [Koch_BiophyComp] Koch, Chr.: Biophysics of Computation. Oxford Univ. Press, 1999.
  [Kohonen-SOM2001] Kohonen, Teuvo: Self-Organizing Maps. 3 A., Springer, 2001.
  [Kohonen_AdaptiveSub] Kohonen, Teuvo, Haski, S.; Lappalainen, H.: Self-Organized Formation of Various Invariant Feature Filters in the Adaptive Subspace SOM. In: Neural Computation, Vol. 9, S. 1321-1344, 1997.
  [Kohonen_AdaptiveSub96] Kohonen, Teuvo: Emergence of invariant Feature Detectors in the Adaptive Subspace Selforganizing Map. In: Biological Cybernetics, 75, S. 281 -291, 1996.
  [Kohonen_ContentMemory] Kohonen, Teuvo: Content Addressable Memories. Springer, 1987.
# [Kohonen_SelfOrgAssM] Kohonen, Teuvo: Self-Organization and Associative Memory. 3A. Springer, 19__.
  [Kohonen_SOM95] Kohonen, Teuvo: Self-Organizing Maps. Springer, 1995.
  [Korn_NNFuzzy] Korn, G.A.: Neural Networks and Fuzzy Logic Control on Personal Computers and Workstations. MIT Press, 1995.
  [Kosko_NNFuzzy] Kosko, B.: Neural Networks and Fuzzy Systems. Prentice Hall, 1992.
  [Kurfe§_Log+NN] Kurfeß, F.: Logic and Reasoning with Neural Models. TR Fachgruppe KI, TU München, 1989.

L

 
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  [Lee_StructureLevelNN] Lee, T.C.; Goodman, J.W.: Structure Level Adaption for Artificial Neural Networks. Kluwer, 1991.
  [LexNeuroSci-1, ..., -4] Lexikon der Neurowissenschaft, in vier Bänden, Spektrum Akad. Verlag, Heidelberg, 2000.
  [Linden_SESAME] Linden, A.: SESAME: Ein objekt- und datenflußorientierter Simulator für Modelle der Neuroinformatik und angrenzender Gebiete. Dissertation, Informatik, Univ. Bielefeld, 1994.
  [Linke_Gehirnverpflanzung] Linke, D.B.: Hirnverpflanzung. Rowolt, 1993.
**   Lippmann, Richard P.; Moody, John E.; Touretzky, David S. (eds.): Advances in Neural Information Processing Systems 3, NIPS 3. San Mateo, Calif., 1991.

M

 
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  [Maass_PulsedNN] Maass, W.; Bishop, C.M.: Pulsed Neural Networks. MIT Press, 1999.
  [MacKay_IPN_1.2.5] MacKay, D.J.C.: Information Theory, Probability and Neural Networks. Draft 1.2.5., 1997.
  [MacKay_NCompu4/92-90] MacKay, D.J.C.: Information-based objective Functions for Active Data Selection. In: Neural Computation, 4, S. 590-604, 1992
  [Mani_ReflexReason] Mani, D.R.; Shastri, L.: Reflexive Reasoning with Multiple Instantiation in a Connectionist Reasoning system with a Type Hierarchy. In: Connection Science, Vol. 5, Nr. 3/4, 1993.
  [Maren_HandbookNNApl] Maren, A.J.; Harston, C.T.; Pap, R.M.: Handbook of Neurak Computing Applications. Academic Press, 1990.
**   Martinetz, Thomas: Selbstorganisierende neuronale Netzwerkmodelle zur Bewegungssteuerung. St. Augustin, 1992.
  [Martinetz_TPN] Martinetz, Th.; Schulten, K.: Topology Representing Networks. In: Neural Networks, Vol. 7, Nr.3, S. 507-522, 1994.
  [Miikkulainen_NLP] Miikkulainen, R.: Subsymbolic Natural Language Processing. MIT Press, 1993.
**   Moody, John E.; Hanson, Steve J.; Lippmann, Richard P. (eds.): Advances in Neural Information Processing Systems 4, NIPS 4. San Mateo, Calif., 1992.
  [Morgan_NNSpeech] Morgan, D.P.; Scofield, C.L.: Neural Networks and Speech Processing. Kluwer, 1991.

N

 
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# [Nigrin_NNPatternRec] Nigrin, A.: Neural Networks for Pattern Recognition. MIT Press, 1993.

O

   
  [Obermayer_AdapNN] Obermayer, K.: Adaptive Neuronale Netze und ihre Anwendung als Modelle der Entwicklung kortikaler Karten. infix, 1993.
  [Obermayer_SelfOrgMap] Obermayer, K.; Sejnowski, T.J. (eds.): Self-Organizing Map Formation. MIT Press, 2001.
**  

Oja, E.: PCA: Algorithms and Applications. In: Proceeding of World Congress on Neural Networks. Portland, Vol. 2, 1993, S. 396 - 400.

**   Omohundro, Stephen M.: The Delaunay triangulation and function learning. TR-90-001, International Computer Sciene Institute, Berkley, 1990. (http://www.icsi.berkeley.edu/ftp/pub/techreports/1990/tr-90-001.pdf).
  [Orr_NNTricks] Orr, G.B.; Müller, K.-R.: Neural Networks: Tricks of the Trade. Springer, 1998.

P

 
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**   Paa§, Gerhard; Kindermann, Jšrg: Bayesian query construction for neural network models. In: Tesauro et al. (1995[331]), NIPS 7, 1995, S. 443 - 450. { 33} (http://nips.djvuzone.org/djvu/nips07/0443.djvu).
**  

Paa§, Gerhard; Kindermann, Jšrg: Konstruktive Datenerhebung mit reflektiven neuronalen Netzen. In: GMD-Spielgel, 2, 1995, S. 37 - 44.

**   Paa§, Gerhard; Kurfe§, Franz (Hrsg.): Wissensverarbeitung mit Neuronalen Netzen. GMD-Studie 221, GMD, Sankt Augustin, 1993.
  [Parks_NNModelling] Parks, R.; Levine, D.S.; Long, D.L. (eds.): Fundamentals of Neural Network Modelling: Neuropsychology and cognitive Neuroschience. MIT Press, 1998.
  [Pawelzik_Nichlin+Hirna] Pawelzik, K.: Nichtlineare Dynamik und Hirnaktivität. Verlag Harri Deutsch, 1991.
  [Perry-NeuroChemistry] Perry, E.; Ashton, H.; Young, A.: Neurochemistry of Consciousness. John Benjamins Publ., 2002.
  [Plutowski_TNN_4/93]

Plutowski, M.; White, H.: Selecting concise training sets from clean data. In: IEEE Transactions on Neural Networks 4 (2), 1993, S. 305 - 318.

**   Plutowski, M.: Selected Training Exemplars for Neural Network Learning. PhD thesis, University of California, San Diego, 1994.
**   Poggio, Tomaso; Girosi, Federico: A theory of networks for approximation and learning. Technical Report AIM-1140, Artificial Intelligence Laboratory and Center for Biological Information Processing, Whitaker College, Massachusetts Institute of Technology, 1989. (ftp://publications.ai.mit.edu/ai-publications/1000-1499/AIM-1140.ps.Z).
  [Pšppel_GrenzenBew] Pöppel, E.: Grenzen des Bewustseins. Insel Verlag, 1997.
# [Pšppel_LustSchmerz] Pöppel, E.: Lust und Schmerz. Sammlung Siedler, 19___.
  [Preckel_DVisu] Preckel, E.: Datenvisualisierung mit selbstorganisierenden Neuronalen Netzen. Diplomarbeit, Institut Mathematische Maschinen und Datenverarbeitung, Uni. Erlangen Nürnberg, 1992.

R

 
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  [Rapp_Assoziation] Rapp, R.: Berechnung von Assoziationen. Hildesheim, 1996.
  [Refences_NN+Capital] Refenes, A.-P.: Neural Networks in the Capital Markets. Wiley & Sons, 1995.
  [Reiss_TemporalSeq] Reiss, M.; Taylor, J.G.: Storing Temporal Sequences. In: Neural Networks, Vol. 4, S. 773-787, 1991.
# [Rethinking_NN] Rethinking Neural Networks
  [Richards_CogNeuro] Richards, J.E.: Cognitive Neuroscience of Attention. Lawrence Erlbaum. 1998.
  [RitterMartinetz_NN] Ritter, Helge; Martinetz, Thomas; Schulten, Klaus: Neuronale Netze - EinfŸhrung in die Neuroinformatik selbstorganisierender Netzwerke. Addison-Wesley, Bonn, 2. Auflage, 1991.
  [Roth_Gehirn+Wirkl] Roth, G.: Das Gehirn und seine Wirklichkeit. Surkamp, 1995.
  [Ruisch_KohoActivMedium] Ruwisch, D.; Bode, M.; Purwins, H.G.: Parallel Hardware Implementation of Kohonens Algorithm with an Active Medium. In: Neural Networks, Vol. 6, S. 1147-1157, 1993.

S

 
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  [Schikuta_ParaNeuDB] Schikuta, E.: Parallelism in the NeuDB-System. Department pf Data Engineering, Univ. Wien.
  [Schildberger_NeuroBehavior] Schildberger, K.; Elsner N.: Neural Basis of Behavioral Adaptions. Fischer Verlag, 1994.
  [Schmidhuber_Raumzeit] Schmidhuber, J.: Dynamische neuronale Netze und das fundamentale raumzeitliche Lernproblem. Dissertation, Inst. f. Informatik, TU München, 1990.
  [Schšlkopf_KernelPCA] Schölkopf, B.; Smola, A.; Müller, K.R.: Nonlinear Component Analysis as a Kernel Eigenvalue Problem. TR44, Max Planck Inst. biolog. Kybernetik, 1996.
  [Scholtes_Dis_NN+IR] Scholtes, Johannes Cornelis: Neural Networks in Natural Language Processing and Information Retrieval. Dissertation, Uni Amsterdam, 1993.
  [Schšneburg-NN90] Schöneburg, E.; Hausen, N.; Gawelczyk, A.: Neuronale Netze. Haar/München, 1990.
  [Schweizer_NN-Compres] Schweizer, L.; Parladori, G.; Sicuranza, G.L.; Marsi, S.: A Fully Neural Approch to Image compression. In: Kohonen, T.; Mäkisara, K.; Simula, O.; Kangas, J. (eds.): Artificial Neural Networks. 1991, S. 815-820.
  [Sejnowski_DistriRep] Sejnowski, T.J.; Abbott, L.: Neural Codes and Distributed Representations. MIT Press, 1999.
  [Siegelman_NNAnalog] Siegelmann, Hava T.: Neural Networks and Analog Computation - Beyond the Turing Limit. BirkhŠuser Verlag, 1999.
  [Skinner_NNMatScience] Skinner, A.J.; Broughton, J.Q.: Neural Networks in computational Material Science: training algorithms. In: Modelling Simmul. Mater Sci. Engineering, 3 371-390, 1995.
  [Smith_NeurComp94] Smith, L.S.; Hancock, J.B. (eds.): Neural Computing and Psychology. NCPW3|94, Springer, 1995.
**  

Sollich, Peter: Asking Intelligent Questions - the Statistical Mechanics of Query Learning. PhD thesis, University of Edinburgh, 1993. (ftp://archive.cis.ohio-state.edu/pub/neuroprose/Thesis/sollich.thesis.tar.Z).

**   Sollich, Peter: Query construction, entropy and generalisation in neural network models. In: Physical Review E 49, 1994, S. 4637 - 4651. (http://www.mth.kcl.ac.uk/~psollich/papers/QueryPREIV.ps.gz).
  [Sperduti_LRAAM] Sperduti, A.: Labeling RAAM. TR-93-029.
  [Stamenov-MirrorNN] Stamenov, M.J.; Gallese, V.: Mirror Neurons and the Evolution of Brain and Language. John Benjamins, 2002.
  [SunBookman_IntegrNNSy] Sun, Ron; Bookman, Lawrence A.: Computational Architectures integrating Neural and Symbolic Processes. Bosten, 1995.
  [Sun_Rules+NN] Sun, Ron: Integrating Rules and Connectionism for robust Comonsense Reasoning. Wiley & Sons, 1994.
  [Sutton _97a] Sutton, R.S.; Barto, A.G.: Reinforcement Learning I: Instruction, 1997.
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Letzte Änderung 26.12.2003