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M. Amiri, R. Brause: Information Based Universal Feature Extraction in Shallow Networks ,International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Volume 31, Issue 06, June 2017

M. Amiri, R. Brause: Information Based Universal Feature Extraction, Proc. 7th International Conference on Machine Vision  (ICMV 2014), Milan 2014

R. Brause, E. Hanisch: An Alarm System for Death Prediction, International Journal of Monitoring and Surveillance Technologies Research, 1(2), 29-39, April-June 2013 29

E. Hanisch, R. Brause, J. Paetz, B. Arlt: Review of A Large Clinical Series: Predicting Death for Patients With Abdominal Septic Shock, Journal of Intensive Care Medicine, January/February 2011 Vol. 26(1): pp.27-33, revised version, doi: 10.1177/0885066610384058

E. Hanisch, R. Brause: Intensivmedizin: Ist der Tod individuell voraussagbar?, Forschung Frankfurt, Jg.28, 1.2010, Goethe-Universität, Frankfurt, Germany 2010, S.61-63

R. Brause: Real-valued Feature Selection by Mutual Information of Order 2, IEEE 21th Int. Conf on Tools with Art. Intell. ICTAI-2009, Newark 2009, IEEE Press 2009, pp. 597-604

F. Heister, R. Brause: Real-valued Feature Selection for process approximation and prediction, Technical Report Nr. 1/09, Computer Science Dep., Goethe University, Frankfurt, Germany 2009

F. Heister: Nonlinear feature selection using the general mutual information, Dissertation, Johann Wolfgang Goethe-Universität, Frankfurt am Main, FB Informatik und Mathematik, Institut für Informatik 2008

J. Fojdl, R. Brause: The Performance of Approximating Ordinary Differential Equations by Neural Nets, in: IEEE 20th Int. Conf on Tools with Art. Intell. ICTAI-2008, Dayton 2008, IEEE Press 2008

B. Ende, R. Brause: Mutual Information based Clustering of Market Basket Data for Profiling Users, in: IEEE 19th Int. Conf on Tools with Art. Intell. ICTAI-2007, Patras 2007, IEEE Press 2007

N. Maglaveras, I. Chouvarda, V. Koutkias, R. Brause (Eds.): Biological and Medical Data Analysis, Proc. 7th International Symposium, ISBMDA 2006, Thessaloniki, Greece, December 7-8, 2006. Lecture Notes in Bioinformatics, LNCS Vol 4345, Springer Verlag Heidelberg, ISBN 978-3-540-68063-5

A. Ünlü, R. Brause, K. Krakow: Handwriting Analysis for Diagnosis and Prognosis of Parkinson’s Disease, in: N.Maglaveras, I.Chouvarda, V. Koutkias, R.Brause (Eds.): Proc. Int. Symp. Biological and Medical Data Analysis, LNCS Vol 4345, Springer Verlag Heidelberg 2006, pp. 441-450

R. Brause: Nature inspired robustness of networks: paper, Nature inspired robustness: paper, slides; Robustness Mechanisms in Biology: paper, slides, Robustness in immune system modeling and sepsis therapy: slides, Robustness in system modeling: slides. Symposium on Nature Inspired Smart Information Systems, Tenerife 2006. MIT, Aachen 2006

R. Brause, E. Hanisch, J.Paetz, B.Arlt : Predicting Death for Abdominal Septic Shock Patients-The results of the MEDAN project in: A. Nierhaus, K.G. Kreymann (Eds.): Sepsis, SIRS, Immune Response - Concepts, Diagnostics and Therapy, Pabst Science Publ., Lengerich 2005, pp. 119-126

R. Brause: Adaptive modeling of biochemical pathways. Int. Journal on Artificial Intelligence Tools Vol13, No.4 (Dec.2004), pp. 851-862

R. Brause: Model selection and adaptation for biochemical pathways. 5th International Symposium on Biological and Medical Data Analysis ISBMDA 2004,
José M. Barreiro, Fernando Martin-Sanchez, Víctor Maojo, et al. (Eds.), Lecture Notes in Computer Science LNCS 3337, Springer Verlag 2004, pp. 439-449

M. Schneider: Ein adaptives Verfahren zur Modellierung und Verifikation der Unterschriftendynamik, Diplomarbeit am Fachbereich Biologie und Informatik, J.W.G.-Universität Frankfurt a.M., 2004

R. Brause:Data driven automatic model selection and parameter adaptation– a case study for septic shock IEEE 16th Int. Conf on Tools with Art. Intell. ICTAI-2004, IEEE Press 2004, pp.278-283, (2004)

R. Brause: Adaptive modeling of biochemical pathways, Abstracts of 6th World Congress on Trauma, Shock, Inflammation and Sepsis, Suppl. to Shock, Vol.21, 2004, p.146

R. Brause, E. Hanisch, J. Paetz, B. Arlt: Neuronal networks for sepsis prognosis - the MEDAN project, Journal für Anästhesie und Intensivbehandlung (11)1-2004, pp.40-43, updated version, Pabst Science Publ., Lengerich 2004

J. Paetz, B. Arlt, K. Erz, K. Holzer, R. Brause, E. Hanisch: Data Quality Aspects of a Database for Abdominal Septic Shock Patients, Journal of Computer Methods and Programs in Biomedicine 75(1), 23-30 (2004)

R. Brause, E. Hanisch, J. Paetz, B. Arlt: The MEDAN project: results and practical meanings, 3. Int. Symposium "Sepsis, SIRS, Immune Response - Concepts, Diagnostics and Therapy", A.Nierhaus, J.Schulte am Esch (Eds.), PABST Science Publishers, Lengerich (Germany) 2003, pp.122-129

R. Brause: Adaptive modeling of biochemical pathways. IEEE 15th Int. Conf on Tools with Art. Intell. ICTAI-2003, IEEE Press 2003, pp.62-68, (2003), "Best paper" award of ICTAI-2003

  J. Paetz : Evolving Score Neural Networks, Proc. of the 1st Indian Int. Conf. on Artificial Intelligence (IICAI 2003), Hyderabad, India

  P. Perner, R. Brause, H. Holzhütter (eds.): Medical Data Analysis, Proc. Of the 4th Int. Symp. On Medical Data Analysis ISMDA 2003, Springer Lecture Notes on Comp.Sc., LNCS 2868, Springer Verlag, Heidelberg 2003, ISBN: 3-540-20282-X

  R. Brause, M. Ueberall: Adaptive Content Mapping for Internet Navigation, in: R.J.Howlett, N.S.Ichalkaranje, L.C.Jain,G.Tonfoni (Eds.): Internet-Based Intelligent Information Processing Systems, World Scientific, Singapore 2003, pp.25-65

J. Paetz : Knowledge Based Approach to Septic Shock Patient Data Using a Neural Network with Trapezoidal Activation Functions, Artificial Intelligence in Medicine, Special Issue: Knowledge-Based Neurocomputing in Medicine, Vol. 28(2), 207-230, 2003

J. Paetz , K. Erz, B. Arlt, E. Hanisch : Die MEDAN-Datenbank: Patienten mit septischem Schock abdominaler Ursache, Zentralblatt der Chirurgie 128(4), 298-303, 2003

B. Arlt: Ein Internet-basiertes Informations- und Alarmsystem für den septischen Schock abdominaler Ursache, in: B.Arlt. et al., Telematik im Gesundheitswesen, S. 11-53, Mabuse-Verlag, Frankfurt 2003, ISBN 3-935964-25-0

R. Brause: About Adaptive State Knowledge Extraction for Septic Shock Mortality Prediction. IEEE 14th Int. Conf on Tools with Art. Intell. ICTAI-2002, IEEE Press 2002, pp.3-8 (invited paper)

J. Paetz: Adaptive Regelgenerierung und ihre Verwendung zur Diagnose des septischen Schocks; Dissertation, Institut für Informatik, J.W.G.-Universität, Frankfurt 2002. Abstract. Anhang: Errata.

J. Paetz, R. Brause: Rule Generation and Model Selection Used for Medical Diagnosis, Journal of Intelligent and Fuzzy Systems, Special Issue, Vol. 12(1): Challenges for Future Intelligent Systems in Biomedicine, IOS Press 2002, pp.69-78

J. Paetz , B. Arlt : A Neuro-Fuzzy Based Alarm System for Septic Shock Patients with a Comparison to Medical Scores, Proc. of the 3rd Int. Symp. of Medical Data Analysis (ISMDA 2002), Rome, Italy, A. Colosimo, A. Giuliani and P. Sirabella (Eds.), LNCS Vol. 2526, Springer-Verlag, 42-52, 2002

J. Paetz: A Note on Core Regions of Membership Functions, Proc. of the 2nd Europ. Symp. on Intelligent Technologies, Hybrid Systems and their Implementation on Smart Adaptive Systems (EUNITE 2002), Albufeira, Portugal, Wissenschaftsverlag Mainz, Abstract p. 43, article on CD-ROM pp. 167-173

R. Brause, F. Hamker, J. Paetz: Septic Shock Diagnosis by Neural Networks and Rule Based Systems; in: Schmitt, M.; Teodorescu, H.-N.; Jain, A.; Jain, A.; Jain, S.; Jain, L.C., (Eds.): Computational Intelligence Processing in Medical Diagnosis, Springer Verlag, New York 2002, pp.323-356

J. Paetz: Selecting the Representative Neuro-Fuzzy Model, Proc. of the 1st Int. Conf. on Fuzzy Systems and Knowledge Discovery (FSKD 2002), Singapore, 737-741, published also on CD-ROM (ISBN 981-04-7521-7)

J. Paetz: Intersection Based Generalization Rules for the Analysis of Symbolic Septic Shock Patient Data, Proc. of the 2nd IEEE Int. Conf. on Data Mining (ICDM 2002), Maebashi City, Japan, IEEE Computer Society Press, 673-676, 2002

J. Paetz, Durchschnittsbasierte Generalisierungsregeln Teil I: Grundlagen, Frankfurter Informatik-Berichte Nr. 1/02, FB Biologie und Informatik, Institut für Informatik, J.W. Goethe-Universität Frankfurt am Main, 2002

J. Paetz, R. Brause: Durchschnittsbasierte Generalisierungsregeln Teil II: Analyse von Daten septischer Schock-Patienten, Frankfurter Informatik-Berichte Nr. 2/02, FB Biologie und Informatik, Institut für Informatik, J.W. Goethe-Universität Frankfurt am Main, 2002

R. Brause: Medical Analysis and Diagnosis by Neural Networks; in: J. Crespo, V. Maojo, F. Martin, Medical Data Analysis, Springer Verlag Berlin Heidelberg 2001 pp.1-13 (invited keynote paper)

J. Paetz, R. Brause: A Frequent Patterns Tree Approach for Rule Generation with Categorical Septic Shock Patient Data; in: J. Crespo, V. Maojo, F. Martin, Medical Data Analysis, Springer Verlag Berlin Heidelberg 2001, pp.207-212

J. Paetz: Metric Rule Generation with Septic Shock Patient Data, Proc. of the 1st IEEE Int. Conf. on Data Mining (ICDM 2001), San Jose, CA, USA, IEEE Computer Society Press, 637-638, 2001

F. Hamker, J. Paetz, S. Thöne, R. Brause, E. Hanisch: Erkennung kritischer Zustände von Patienten mit der Diagnose "Septischer Schock" mit einem RBF-Netz, Internal Report 4/00, FB Informatik, Universität Frankfurt a.M., 2000

R. Brause, E. Hanisch, (Eds.) Medical Data Analysis, Proc. First International Symposium, ISMDA 2000 Frankfurt, Germany, September 29-30, Lecture Notes on Computer Science LNCS 1933, Springer Verlag, Heidelberg 2000, ISBN: 3-540-41089-9

R. Brause, B. Arlt, E. Tratar: MASCOT: A Mechanism for Attention-based Scale-Invariant Object Recognition in Images, Internal Report 2/00, FB Informatik, Universität Frankfurt a.M., 2000

J. Paetz, F. Hamker, and S. Thöne: About the Analysis of Septic Shock Patient Data, Proc. of the 1st Int. Symp. of Medical Data Analysis (ISMDA 2000), Frankfurt am Main, Germany, R. Brause, E. Hanisch (Eds.), LNCS Vol. 1933, Springer-Verlag 2000, pp.130-137

R. Brause, F. Friedrich: A Neuro-Fuzzy Approach as Medical Interface, European Symp. on Art. Neural Networks, ESANN 2000, D-Facto, Brussels 2000, pp. 201-206

R. Brause, B. Arlt, E. Tratar: Project SEMACODE: A Scale-invariant Object Recognition System for Content-based Queries in Image Databases Internal Report 11/99, FB Informatik, Universität Frankfurt a.M., 1999

R. Brause, T. Langsdorf, M. Hepp: Credit Card Fraud Detection by Adaptive Neural Data Mining, Internal Report 7/99, FB Informatik, Universität Frankfurt a.M., 1999

R. Brause, T. Langsdorf, M.Hepp: Neural Data Mining for Credit Card Fraud Detection, IEEE Int. Conf on Tools with Art. Intell. ICTAI-99, IEEE Press 1999, pp.103-106

U. Pietruschka, R. Brause: Using growing RBF nets in Rubber Industry Process Control, Neural Computing & Applications, Vol 8 No. 2, Springer Verlag 1999, pp.95-105

R. Brause: Revolutionieren Neuronale Netze unsere Vorhersagefähigkeiten? , Zentralblatt für Chirurgie 124, 1999, S. 692-698 (invited paper)

und in: Workshop Epidemiologie der Sepsis - Welche Patienten überleben? Klinik für Allgemeinchirurgie, Klinikum der J.W.Goethe-Universität, Frankfurt a.M. 1998

   B. Arlt, R. Brause: Image Encoding by Principal Independent Components Proc. Künstliche Intelligenz KI-98, Springer Verlag 1998

   B. Arlt, R. Brause: The Principal Independent Components of Images, Int. Conf. Art. Neural Networks ICANN-98, Skövde, Sweden 1998

R. Brause, U. Pietruschka: Adaptive Control in Rubber Industry, (117KB) Int. Journ. of Occ. Safety and Ergonomics (JOSE), Ablex Publ. Corp., Vol.4 No.3, 1998, pp.253-269

R. Brause, M. Rippel: Noise Suppressing Sensor Encoding and Neural Signal Orthonormalization, IEEE Transact. on Neural Networks Vol.9, No.4, 1998, pp.613-628

B. Arlt, R. Brause: The Principal Independent Components of Images, Internal Report 1/98, FB Informatik, Universität Frankfurt a.M., 1998

E. Hanisch, M. Büssow, R. Brause, A. Encke: Individuelle Prognose bei kritisch kranken Patienten mit septischem Schock durch ein neuronales Netz?, Der Chirurg, Vol.69, (1998), S.77-81

M. Büssow, S. Wade, R. Brause, E. Hanisch: Prognostische Beurteilung chirurgischer Intensivpatienten mit einem Neuronalen Netz. Deutscher Chirurgenkongreß 1997, München

R. Brause: Implementing the SCAN Language by Neural Networks; IEEE Int. Joint Symposia on Intelligence and Systems IJSIS-96, Rockville 1996, pp.242-251

U. Pietruschka, R. Brause: Using RBF nets in Rubber Industry Process Control; Int. Conf. on Art. Neural Networks ICANN-96, Bochum 1996, pp.605-610, LNCS 1112, Springer Verlag 1996

R. Brause : Sensor Encoding using Lateral inhibited, Self-organized Cellular Neural Networks ; Neural Networks Vol.9, No.1, pp.99-120, 1996

R. Brause : Self-organized Learning in Multi-Layer Networks, Int. Journal on Art. Intell. Tools, Vol.4, No.4, pp.433-451, 1995

R. Brause, J. Glitsch : A Spectral Multi-resolution Image Encoding Network; IEEE Int. Conf. on Tools with Art. Intell. TAI-95 ,pp. 138-141, 1995

R. Brause : Self-organized Learning in Multi-Layer Networks, First Int. IEEE Symposium on Intelligence in Neural and Biol. Systems, Washington DC, May 1995

N.G. Bourbakis, R. Brause and C. Alexopoulos : Scan Image Compression/Encryption Hardware System; in: Arturo A. Rodriguez; Robert J. Safranek; Edward J. Delp (Eds.): Proc. SPIE Conf. on Electronic Imaging, Digital Video Compression: Algorithms and Technologies. Vol. 2419, pp. 419-428, 1995, San Jose, CA

R. Brause: Cascaded Vector Quantization by Non-linear PCA Network layers; IEEE Int. Conf. on Tools with Art. Intell. TAI-94, Nov. 1994

R. Brause : A VLSI-Design of the Minimum Entropy Neuron; in: J.Delgado-Frias, W.Moore (Eds.): VLSI for Artificial Intelligence and Neural Networks, pp.53-60, Plenum Press, New York 1994

R. Brause :Picture encoding using Self-Organized Cellular Neural Nets, Int. Conf. on Art. Neural Nets ICANN '94, pp.1125-1128, Springer Verlag 1994

R. Brause : An Approximation Network with Maximal Transinformation, Int. Conf. on Art. Neural Nets ICANN '94, pp.701-703, Springer Verlag 1994

R. Brause : The error-bounded Descriptional Complexity of Approximation Networks Neural Networks, Vol.6, pp.177-187, 1993

R. Brause : A Symmetrical Lateral Inhibition Network for PCA and Feature Decorrelation, Proc. ICANN-93, pp. 486-489, Springer Verlag 1993

R. Brause : Transform Coding by Lateral Inhibited Neural Nets, IEEE Int. Conf. on Tools with Art. Intelligence TAI-93, pp.14-21, 1993

R. Brause : The Minimum Entropy Network; Interner Bericht 1/92 des Fachbereichs Informatik der J.W. Goethe Universität, Frankfurt a.M., 1992,

R. Brause : The Minimum Entropy Network; IEEE Proc. Int. Conf. on Tools with Artificial Intelligence TAI-92, pp.85-92, 1992

R. Brause : The Minimum Entropy Neuron- a new building block for clustering transformations, in: Int.Conf. Art. Neural Networks ICANN; I.Aleksander, J.Taylor (eds.), pp. 787-790, Elsevier Sc.Publ., Amsterdam 1992

W. Simantzik and R. Brause : Classification and Reproduction of Time Sequences without Preprocessing, in: Art. Neural Networks 2; I.Aleksander, J.Taylor (eds.), pp. 1095-1098, Elsevier Sc.Publ., Amsterdam 1992

R. Brause : Determination of Neural Network Parameters by Information Theory, Int. Journal on Artificial Intelligence Tools, Vol.1,No.2, pp.205-227, World Sc. Publ., Singapure 1992

R. Brause : Optimal Information Distribution and Performance in Neighbourhood-conserving Maps for Robot Control, Int. Journal of Computers and Artificial Intelligence, Vol 11, No. 2, pp.173-199, 1992

R. Brause : Approximator Networks and the Principle of Optimal Information Distribution; Interner Bericht 1/91 des Fachbereichs Informatik der J.W. Goethe Universität, Frankfurt a.M., 1991,
and in: Art. Neural Networks 1; T.Kohonen et.al.(eds.), pp. 43-48, Elsevier Sc.Publ., Amsterdam 1991

R. Brause : The Determination of Neural Network Parameters by Information Theory, IEEE Proc. Int. Conf. on Tools for Artificial Intelligence TAI-91, San Jose 1991

R. Brause : Optimal Performance and Storage Requirements of Neighbourhood-conserving Mappings for Robot Control, IEEE Proc. Int. Conf. on Tools for Artificial Intelligence TAI-90, Washington  D.C. 1990,
and in: Proc. Int. Neural Network Conf. INNC-90, Paris 1990

R. Brause : Parallelarbeit und Fehlertoleranz in Multiprozessorsystemen, Interner Bericht, Institut für Informatik, Universität Frankfurt a.M., 1990

R. Brause : Übersicht über das Parallelisierungskonzept von Attempto 2, Interner Bericht 1, Institut für Informatik, Universität Frankfurt a.M., 1990

R. Brause : Das Fehlertoleranzkonzept von Attempto 2, Interner Bericht 2, Institut für Informatik, Universität Frankfurt a.M., 1990

R. Brause : Performance of Topology-conserving Maps for the Learning of Robot Manipulator Control, in: I.Plander (Editor), Artificial Intelligence and Information-Control Systems of Robots AIICSR-89, Elsevier Sc. Publ.. 1989

R. Brause : Performance and Storage Requirements of Topology-conserving Maps for Robot Manipulator Control, Internal Report 5/89 of Fachbereich Informatik, J.W. Goethe Universität, Frankfurt a.M., 1989

M. Dal Cin, R. Brause, W. Günter: Fehlertoleranz verlangt Mehrfachansatz, Focus 3, Computerwoche 11/8 1989

J. Lutz , R. Brause , M. Dal Cin, K. Kammers, Th. Philipp : Die Erweiterungen der Attempto-2 Laufzeitbibliothek, Interner Bericht 2/89 des Fachbereichs Informatik der J.W. Goethe Universität, Frankfurt a.M., 1989

J. Lutz , R. Brause , M. Dal Cin, Th. Philipp : Parallelisierungskonzept für Attempto-2, Interner Bericht 1/89 des Fachbereichs Informatik der J.W. Goethe Universität, Frankfurt a.M., 1989

R. Brause : Neural Network Simulation using INES, IEEE Proc. Int. Conf. on Tools for Artificial Intelligence TAI-89, Washington D.C. 1989

R. Brause : Fault-Tolerance in Non-linear Neural Networks, in: R.Valk (Editor), Vernetzte und komplexe Informatik-Systeme, GI-18.Jahrestagung II, Hamburg, Informatik Fachberichte 188, pp. 412-433, Springer-Verlag 1988

R. Brause : Pattern Recognition and Fault-Tolerance in Non-linear Neural Networks, Abstracts of Int. Conf. Neural Networks, Boston, Pergamon press 1988,
and Full Paper.

R. Brause : Mustererkennung mit verteiltem, assoziativen Speicher, Proc. Workshop Kennektionismus, St.Augustin, Arbeitspapiere der GMD, 1988

R. Brause : Fehlertoleranz in intelligenten Benutzerschnittstellen, Informationstechnik it, (30)3, pp.219-224, Oldenburg Verlag München 1988

R. Brause : Prozessoren tauschen Nachrichten über Dual-ported RAMs aus, VMEbus, Franzis Verlag München, April 1988

R. Brause : Simulation eines fehlertoleranten Multi-Mikroprozessorsystems unter Unix, Proc.  Workshop  der Arbeitsgruppe  Simulation  von Systemen ASIM der GI, München 1987

M. Dal Cin , R. Brause, J. Lutz, E. Dilger, Th. Risse : Attempto: An experimental fault-tolerant multiprocessor system, Microprocessing and Microprogramming 20, pp.301-308, 1987

M. Dal Cin , R. Brause, J. Lutz, E. Dilger, Th. Risse : Attempto: An experimental fault-tolerant multiprocessor system, Interner Bericht 5/86 des Fachbereichs Informatik der J.W. Goethe Universität, Frankfurt a.M., 1986

M. Dal Cin, R. Brause, E. Dilger, J. Lutz, Th. Risse: ATTEMPTO - A  Testable Experimental  Multiprocessor  System  with Fault-tolerance IEEE  Computer Architecture Technical Committee,  Vol. June 1985

R. Brause : Design eines fehlertoleranten Rechners, Computer Magazin 11, 1985

T. Risse,  R. Brause, M. Dal Cin, E. Dilger, J. Lutz: Entwurf und Struktur einer Betriebssystemschicht zur Implementierung von Fehlertoleranz, Tagungsbericht Fehlertolerierende Rechensysteme, Bonn, Informatik- Fachberichte 84, Springer Verlag 1984

R. Brause : Selbstdiagnose von Mehrrechnersystemen bei nichtvollständiger Vernetzung, Dissertation, Institut für Informationsverarbeitung, Fakultät für Physik, Eberhard-Karls-Universität Tübingen, 1983

E. Ammann, R. Brause, M. Dal Cin, E. Dilger, J. Lutz, Th. Risse: Attempto: A Fault-tolerant Multiprocessor Working Station; Design and Concepts. IEEE Proc. Int. Conf. Fault-Tolerant Comp. Syst. FTCS-13, Milano 1983

E. Ammann, Th. Risse, R. Brause, M. Dal Cin, E. Dilger, J. Lutz : Theoretical Aspects of Test and Diagnosis in Attempto. Proc. Fault-Tolerant Systems and Diagnostics FTSD83, Brno (Brünn), pp. 84-87, Czechoslovakia 1983

R. Brause, E. Ammann, M. Dal Cin, E. Dilger, J. Lutz, Th. Risse : Konzepte des fehlertoleranten Arbeitsplatzrechners ATTEMPTO, in: E.Maehle, E.Schmitter (Hrsg), Workshop fehlertolerante Mehrprozessorsysteme und Mehrrechnersysteme, Arbeitsberichte des Instituts für mathemat. Maschinen und Datenverarbeitung, Erlangen 1983

R. Brause, E. Ammann, M. Dal Cin, E. Dilger, J. Lutz, Th. Risse : Softwarekonzepte des  fehlertoleranten Arbeitsplatzrechners ATTEMPTO, ACM Proc. of Microcomputing II, Teubner Verlag Stuttgart 1983, p.328-341

R. Brause, E. Dilger, Th. Risse : Diagnosing Algorithms and Learning, in: M.Dal Cin, E.Dilger (Eds): Self-Diagnosis and Fault-Tolerance, Attempto Verlag, Tübingen 1981

R. Brause : Catastrophic Effects in Pattern Recognition, in: W.Güttinger, Eikemeier (Eds), Structural Stability in Physics, Springer Verlag 1979

R. Brause : Mustererkennung mit stochastischem Lernalgorithmus, Diplomarbeit, Institut für Informationsverarbeitung, Fakultät für Physik, Eberhard-Karls-Universität Tübingen, 1978