Journal Publications (2014 and earlier)

Type Author Title Publication Information Date Pages/Volume/Issue Links
Jrn H.T. Siegelmann and R. Freund Bulletin of European Association for Theoretical Computer Science EATCS 2014 number 114, pp. 265-269 pdf
Jrn A. Tal, N. Peled, and H. T. Siegelmann Biologically inspired load balancing mechanism in neocortical competitive learning Frontiers in Neural Circuits 2014 doi: 10.3389/fncir.2014.00018 pdf
Jrn J. Cabessa, H.T. Siegelmann The Super-Turing Computational Power of Plastic Recurrent Neural Networks International Journal of Neural Systems 2014 24, 1450029 pdf
Jrn D. Nowicki, P. Verga, H.T. Siegelmann Modeling Reconsolidation in Kernel Associative Memory PLOS One 2013 8(8) e68189 pdf
Jrn H. T. Siegelmann Turing on Super-Turing and Adaptivity Progress in Biophysics and Molecular Biology 2013 S0079-6107(13)00027-8 pdf
Jrn E. Kagan, A. Rybalov, H. T. Siegelmann, and R. Yager Probability-generated aggregators International Journal of Intelligent Systems 2013 28(7): 709-727 -
Jrn J. Cabessa and H. T. Siegelmann The Computational Power of Interactive Recurrent Neural Networks Neural Computation 2012 24(4): 996-1019 pdf
Jrn Frederick C. Harris, Jr., Jeffrey L. Krichmar, Hava Siegelmann, Hiroaki Wagatsuma Biologically-Inspired Human-Robot Interactions – Developing More Natural Ways to Communicate with our Machines IEEE Transactions on Autonomous Mental Development (editorial) 2012 4(3),190-191 -
Jrn Jean-Philippe Thivierge, Ali Minai, Hava Siegelmann, Cesare Alippi, Michael Geourgiopoulos A year of neural network research: Special Issue on the 2011 International Joint Conference on Neural Networks Neural Networks (editorial) 2012 32,1-2 -
Jrn H. T. Siegelmann Addiction as a Dynamical Rationality Disorder Frontiers of Electrical and Electronic Engineering (FEE) in China 2011 1(6),151-158 pdf
Jrn H. T. Siegelmann Complex Systems Science and Brain Dynamics: A Special Topic Frontiers in Computational Neuroscience 2010 10.3389 -
Jrn L. Glass and H. T. Siegelmann Logical and symbolic analysis of robust biological dynamics Current Opinion in Genetics & Development 20 2010 644-649 -
Jrn H.T. Siegelmann and L.E. Holzman Neuronal integration of dynamic sources: Bayesian learning and Bayesian inference Chaos 20 2010 037112 pdf
Jrn D.V. Nowicki, H.T. Siegelmann Flexible Kernel Memory PLOS One 5(6) 2010 e10955 pdf
Jrn M.M. Olsen, N. Siegelmann-Danieli, H.T. Siegelmann Dynamic Computational Model Suggests that Cellular Citizenship is Fundamental for Selective Tumor Apoptosis PLOS One 5(5) 2010 e10637 pdf
Jrn K. Tu, D. Cooper, H.T. Siegelmann Memory reconsolidation for natural language processing Cogn Neurodyn 3 2009 365-372 pdf
Jrn A. Z. Pietrzykowski, R. M. Friesen, G. E. Martin, S.I. Puig, C. L. Nowak, P. M. Wynne, H. T. Siegelmann, S. N. Treistman Post-transcriptional regulation of BK channel splice variant stability by miR-9 underlies neuroadaptation to alcohol Neuron 59(2) 2008 274-287 pdf
Jrn Lu, S., Becker, K.A., Hagen, M.J., Yan, H., Roberts, A.L., Mathews, L.A., Schneider, S.S., Siegelmann, H.T., Tirrell, S.M., MacBeth, K.J., Blanchard, J.L. and Jerry, D.J. Transcriptional responses to estrogen and progesterone in Mammary gland identify networks regulating p53 activity Endocrinology 2008 - pdf
Jrn H.T. Siegelmann Analog-Symbolic Memory that Tracks via Reconsoliation Physica D 237(9) 2008 1207-1214 pdf
Jrn M.M. Olsen, N. Siegelmann-Danieli and H.T. Siegelmann Robust Artificial Life Via Artificial Programmed Death Artificial Intelligence 172(6-7) 2008 884-898 pdf
Jrn F. Roth, H.T. Siegelmann and R. J. Douglas The Self-Construction and -Repair of a Foraging Organism by Explicitly Specified Development from a Single Cell Artificial Life 13(4) 2007 347-368 pdf
Jrn S. Sivan, O. Filo and H. Siegelman Application of Expert Networks for Predicting Proteins Secondary Structure Biomolecular Engineering, Volume 24, Issue 2 2007 237-243 pdf
Jrn W. Bush and H.T. Siegelmann Circadian Synchrony in Networks of Protein Rhythm Driven Neurons Complexity Volume 12, Issue 1 2006 67-72 pdf
Jrn T. Leise and H Siegelmann Dynamics of a multistage circadian system Journal of Biological Rhythms, 21:4 2006 314-323 pdf
Jrn L. Glass, T. J. Perkins, J. Mason, H. T. Siegelmann and R. Edwards Chaotic Dynamics in an Electronic Model of a Genetic Network Journal of Statistical Physics Volume 121 Numbers 5/6 2005 969-994 pdf
Jrn Loureiro, O. and Siegelmann, H. Introducing an Active Cluster-Based Information Retrieval Paradigm Journal of the American Society for Information Science and Technology, vl 56, n. 10 2005 1024-1030 pdf
Jrn A. Roitershtein, A. Ben-Hur and H.T. Siegelmann On Probabilistic Analog Automata Theoretical Computer Science, 320(2-3) 2004 449-464 pdf
Jrn A. Ben-Hur, H.T. Siegelmann Computation in Gene Networks Chaos: An Interdisciplinary Journal of Nonlinear Science, 14(1) 2004 145-151 pdf
Jrn A. Ben-Hur, J. Feinberg, S. Fishman and H. T. Siegelmann Random matrix theory for the analysis of the performance of an analog computer: a scaling theory Phys. Lett. A. 323(3-4) 2004 204-209 pdf
Jrn A. Ben-Hur, J. Feinberg, S. Fishman and H. T. Siegelmann Probabilistic analysis of a differential equation for linear programming Journal of Complexity, 19(4) 2003 474-510 pdf
Jrn J. P. Neto, H. T. Siegelmann, and J. F. Costa Symbolic processing in neural networks Journal of the Brazilian Computer Society, 8(3) 2003 - pdf
Jrn S. Eldar, H. T. Siegelmann, D. Buzaglo, I. Matter, A. Cohen, E. Sabo, J. Abrahamson Conversion of Laparoscopic Cholecystectomy to open cholecystectomy in acute cholecystitis: Artificial neural networks improve the prediction of conversion World Journal of Surgery, 26(1) 2002 79-85 pdf
Jrn A. Ben-Hur, H.T. Siegelmann and S. Fishman. A Theory of Complexity for Continuous Time Systems. Journal of Complexity 18(1) 2002 51-86 pdf
Jrn H.T. Siegelmann Neural and Super-Turing Computing Minds and Machines 13(1) 2003 103-114 pdf
Jrn A. Ben-Hur, D. Horn, H.T. Siegelmann and V. Vapnik Support Vector Clustering Journal of Machine Learning Research 2 2001 125-137 pdf
Jrn H.T. Siegelmann A., Ben-Hur, S. Fishman Comments on Attractor Computation International Journal of Computing Anticipatory Systems, D.M. Dubois, ed. 2000 - pdf
Jrn R. Edwards, H.T. Siegelmann, K. Aziza and L. Glass Symbolic dynamics and computation in model gene networks Chaos 11(1) 2001 160-169 pdf
Jrn H. Lipson and H.T. Siegelmann Clustering Irregular Shapes Using High-Order Neurons Neural Computation 12(10) 2000 2331-2353 pdf
Jrn D. Lange, H.T. Siegelmann, H. Pratt, and G.F. Inbar Overcoming Selective Ensemble Averaging: Unsupervised Identification of Event-Related Brain Potentials IEEE Transactions on Biomedical Engineering, 47(6) 2000 822-826 pdf
Jrn H. Karniely and H.T. Siegelmann Sensor Registration Using Neural Networks IEEE Transactions on Aerospace and Electronic Systems, 36(1) 2000 85-98 pdf
Jrn H.T. Siegelmann, Stochastic Analog Networks and Computational Complexity Journal of Complexity, 15(4) 1999 451-475 pdf
Jrn H.T. Siegelmann, A. Ben-Hur and S. Fishman Computational Complexity for Continuous Time Dynamics Physical Review Letters, 83(7) 1999 1463-1466 pdf
Jrn H.T. Siegelmann and M. Margenstern Nine Switch-Affine Neurons Suffice for Turing Universality Neural Networks, 12 1999 593-600 pdf
Jrn R. Gavaldà and H.T. Siegelmann Discontinuities in Recurrent Neural Networks Neural Computation, 11(3) 1999 715-745 pdf
Jrn H.T. Siegelmann and S. Fishman Analog Computation with Dynamical Systems Physica D, 120 1998 120--214 pdf
Jrn A. Galperin, Y. Kimhi, E. Nissan, and H.T. Siegelmann FUELCON's Heuristics, their Rationale, and their Representations The New Review of Applied Expert Systems, 4 1998 163-176 abstract
Jrn Joachim Utans, John Moody, Steve Rehfuss, and Hava Siegelmann Input Variable Selection for Neural Networks: Application to Predicting the U.S. Business Cycle Proceedings of Computational Intelligence in Financial Engineering, IEEE Press 1995 118-122 pdf
Jrn H.T. Siegelmann, E. Nissan, and A. Galperin A Novel Neural/Symbolic Hybrid Approach to Heuristically Optimized Fuel Allocation and Automated Revision of heuristics in Nuclear Engineering Advances in Engineering Software, 28(9) 1997 581-592 pdf
Jrn J.L. Balcázar, R. Gavaldà, and H.T. Siegelmann Computational Power of Neural Networks: A Characterization in Terms of Kolmogorov Complexity IEEE Transactions on Information Theory, 43(4) 1997 1175-1183 pdf
Jrn H.T. Siegelmann, B.G. Horne, and C.L.Giles Computational Capabilities of Recurrent NARX Neural Networks IEEE Transaction on Systems, Man and Cybernetics-part B: Cybernetics, 27(2) 1997 208-215 pdf
Jrn E. Nissan, H.T. Siegelmann, A. Galperin, and S. Kimhi, Upgrading Automation for Nuclear Fuel In-Core Management: From the Symbolic Generation of Configurations, to the Neural Adaptation of Heuristics, Engineering with Computers, 13(1) 1997 1-19 pdf
Jrn O. Frieder and H.T. Siegelmann Multiprocessor Document Allocation: A Genetic Algorithm Approach IEEE Transactions on Knowledge and Data Engineering, 9(4) 1997 640-642 pdf
Jrn H.T. Siegelmann and C.L. Giles The Complexity of Language Recognition by Neural Networks Journal of Neurocomputing; Special Issue Recurrent Networks for Sequence Processing, Editors: M. Gori, M. Mozer, A.H. Tsoi, W. Watrous, 15(3-4) 1997 327-345 pdf
Jrn H.T. Siegelmann, On NIL: The Software Constructor of Neural Networks Parallel Processing Letters, 6(4) 1996 575-582 abstract
Jrn H.T. Siegelmann The Simple Dynamics of Super Turing Theories Theoretical Computer Science, 168(2)(special issue on UMC) 1996 461-472 pdf
Jrn H.T. Siegelmann Recurrent Neural Networks and Finite Automata Journal of Computational Intelligence, 12(4) 1996 567-574 pdf
Jrn J. Kilian and H.T. Siegelmann The Dynamic Universality of Sigmoidal Neural Networks Information and Computation, 128(1) 1996 45-56 pdf
Jrn H.T. Siegelmann Analog Computational Power Science, 271(19) 1996 - pdf
Jrn B. DasGupta, H.T. Siegelmann and E. Sontag On the Complexity of Training Neural Networks with Continuous Activation Functions IEEE Transactions on Neural Networks, 6(6) 1995 1490-1504 pdf
Jrn H.T. Siegelmann Computation Beyond the Turing Limit Science, 238(28) 1995 - pdf
Jrn H.T. Siegelmann and E.D. Sontag On the Computational Power of Neural Nets, Journal of Computer System Sciences, 50(1) 1995 132-150 pdf
Jrn H.T. Siegelmann and E.D. Sontag Analog Computation via Neural Networks Theoretical Computer Science, 131 1994 331-360 pdf
Jrn H.T. Siegelmann and E.D. Sontag Turing Computability with Neural Nets Applied Mathematics Letters, 4(6) 1991 77-80 pdf