Bibliography (Ordered by Author)
(Re-order by Date)

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1. Aberth, O. (1968) Analysis in the Computable Number Field. J. ACM 15, pp. 275-299.
    
2. Abramson, F.G. (1971) Effective Computation over the Real Numbers. Twelfth Annual IEEE Symposium on Switching and Automata Theory, Northridge, CA.
    
3. Adamyan, V.A., Calude, C.S., and B.S. Pavlov. Transcending the limits of Turing computability. In T. Hida, K. Saitô, S. Si (ed.). Quantum Information Complexity. Proceedings of Meijo Winter School 2003, World Scientific, Singapore, 2004, pp. 119-137.
    
4. Ambrose A. (1935) Finitism in Mathematics I. Mind 35, pp. 186-203.
    
5. Ambrose A. (1935) Finitism in Mathematics II. Mind 35, pp. 317-340.
    
6. Bains, S. (2003) Intelligence as Physical Computation. AISB Journal 1(3), July 2003, pp. 225-240.
    
7. Bains, S. & J. Johnson (2000) 'Noise, physics and non-Turing computation' in: Joint Conference on Information Systems, Atlantic City, 28 February - March 3, 2000. Also available from http://citeseer.nj.nec.com/298231.html.
    
8. Balcàzar, J.L., R. Gavaldà & H.T. Siegelmann (1997) Computational Power of Neural Networks: A Characterization in Terms of Kolmogorov Complexity. IEEE Trans. on Information Theory 43(4), pp. 1175-1183.
    
9. Ballard, D.H. (1997) An Introduction to Natural Computation. Cambridge, MA: MIT Press.
    
10. Benioff, P. (1980) The Computer as a Physical System: A Microscopic Quantum Mechanical Hamiltonian Model of Computers as Represented by Turing Machines. J. Statistical Physics 22, pp. 563-591.
     
11. Bennett, C.H. (1993) Teleporting an Unknown Quantum State via Dual Classical and Einstein-Podolsky-Rosen Channels. Physics Review Letters 70, pp. 1895-1898.
     
12. Bennett, C.H. (1995) Quantum Information and Computation. Physics Today 48(10), pp. 24-30.
     
13. Blake R.M. (1926) The Paradox of Temporal Process. J. Philosophy 23, pp. 645-654.
     
14. Blum, L., F. Cucker, M. Shub and S. Smale (1998) Complexity and Real Computation. New York: Springer.
     
15. Blum, L., M. Shub & S. Smale (1989) On a Theory of Computation and Complexity over the Real Numbers: NP-Completeness, Recursive Functions and Universal Machines. Bulletin of the American Mathematical Society 21, pp. 1-46.
     
16. Boolos, G.S. and R.C. Jeffrey. (1974) Computability and Logic. Cambridge: CUP.
     
17. Boothroyd, D. (2001, Tuesday 12 June) Beyond Computing New Electronics 34(11), pp. 16-18.
     
18. Bringsjord, S. (forthcoming) Super-Minds: A Defense of Uncomputable Cognition.
     
19. Bringsjord, S. (1998) 'Philosophy and "Super" Computation' in: T. Ward & Bringsjord, S. (1997) 'An Argument for the Uncomputability of Infinitary Mathematical Expertise' (in: P. Feltovitch, K. Ford and R. Hoffman (eds.) Expertise in Context). AAAI Press.
     
20. Bringsjord, S. and Zenzen, M. (2002) Toward a Formal Philosophy of Hypercomputation. Minds and Machines 12, pp. 241–258.
     
21. Bringsjord S. & Arkoudas K. (2004) The modal argument for hypercomputing minds. Theoretical Computer Science 317, pp. 167-190.
     
22. Bush V. (1931) The Differential Analyser: A New Machine for Solving Differential Equations. J. Franklin Institute 212, pp. 447-488.
     
23. Bush V. (1936) Instrumental Analysis. Bull. AMS 42, pp. 649-669.
     
24. Bush V. & S.H. Caldwell (1945) A New Type of Differential Analyser. J. Franklin Institute 240, pp. 255-326.
     
25. Bynum & J.H. Moor (eds.), The Digital Phoenix: How Computers are Changing Philosophy. Oxford: Blackwell.
     
26. Calude, C.S. (2002) Incompleteness, Complexity, Randomness and Beyond. Minds and Machines 12, pp. 503–517.
     
27. Calude, C.S. (2005) Algorithmic randomness, quantum physics, and incompleteness. In: M. Margenstern (ed.). Proceedings of the Conference "Machines, Computations and Universality" (MCU'2004), Lectures Notes in Computer Science 3354, Springer, Berlin, pp. 1-17.
     
28. Calude C.S. & M.J. Dinneen (2005) Is quantum randomness algorithmic random? A preliminary attack. In: S. Bozapalidis, A. Kalampakas, G. Rahonis (eds.). Proceedings 1st International Conference on Algebraic Informatics, Aristotle University of Thessaloniki, October, 2005, pp. 195--196.
     
29. Calude, C.S., Dinneen, M.J. & K. Svozil (2000) Reflections on quantum computing. Complexity 6(1), pp. 35--37.
     
30. Calude, C.S. & B. Pavlov (2002) Coins, quantum measurements, and Turing's barrier. Quantum Information Processing 1(1-2), pp. 107-127.
     
31. Calude, C.S. & K. Svozil (2006) Quantum Randomness and Value Indefiniteness. CDMTCS Research Report 291, 2006, 12 pp.
     
32. Church A. (1936) An Unsolvable Problem of Elementary Number Theory. Amer. J. Math. 58, pp. 345-363.
     
33. Church A. (1940) On the Concept of a Random Sequence. Bull. AMS 46, pp. 130-135.
     
34. Churchland, P.M. and P.S. Churchland (1990) Could a Machine Think? Scientific American 262(1), pp. 26-31.
     
35. Cleland, C.E. (1993) Is the Church-Turing Thesis True? Minds and Machines 3, pp.283-312.
     
36. Cleland, C.E. (2002) On Effective Procedures. Minds and Machines 12, pp. 159–179.
     
37. da Costa, N.C.A. & F.A. Doria (1991) Classical Physics and Penrose’s Thesis. Foundations of Physics Letters 4, pp. 363-374.
     
38. Copeland, A.H. (1940) '[Review of] Alonzo Church. On the Concept of a Random Sequence. Bulletin of the American Mathematical Society, vol 46 (1940), pp. 130-155'. J. Symbolic Logic 5(2), pp. 71-72.
     
39. Copeland, B.J. (online) 'The Church-Turing Thesis' in: E. Zalta (ed.) The Stanford Encyclopaedia of Philosophy.
     
40. Copeland, B.J. (1997) The Broad Conception of Computation. American Behavioral Scientist 40, pp. 690-716.
     
41. Copeland, B.J. (1998) Super Turing-Machines. Complexity 4, pp. 30-32.
     
42. Copeland, B.J. (1998) Turing's O-Machines, Penrose, Searle, and the Brain. Analysis 58, pp.128-138.
     
43. Copeland, B.J. (1998) 'Even Turing Machines Can Compute Uncomputable Functions' in: C. Calude, J. Casti, and M. Dinneen (eds.), Unconventional Models of Computation. London: Springer-Verlag,150-164.
     
44. Copeland, B.J. (2000) Narrow Versus Wide Mechanism. Journal of Philosophy 96, pp. 5-32.
     
45. Copeland, B.J. (2001) 'Colossus and the Dawning of the Computer Age' in: R. Erskine and M. Smith, ed. Action This Day. London: Bantam Books.
     
46. Copeland, B.J. (2001, online) 'Modern History of Computing' in: E. Zalta (ed.) The Stanford Encyclopaedia of Philosophy.
     
47. Copeland, B.J. (2002) Accelerating Turing Machines. Minds and Machines 12, pp. 281-301.
     
48. Copeland, B.J. (2002) Hypercomputation. Minds and Machines 12, pp. 461-502.
     
49. Copeland, B.J. & D. Proudfoot (1999) Alan Turing's Forgotten Ideas in Computer Science. Scientific American 280 (April 1999), pp. 99-103.
     
50. Copeland, B.J. & D. Proudfoot (1999) The Legacy of Alan Turing Mind 108 pp. 187-195.
     
51. Copeland, B.J. & D. Proudfoot (2000) What Turing Did After He Invented the Universal Turing Machine. Journal of Logic, Language, and Information, pp. 1-19.
     
52. Copeland, B.J. & R. Sylvan (1999) Beyond the Universal Turing Machine. Australasian Journal of Philosophy 77, pp. 46-66.
     
53. Cotogno P. (2003) Hypercomputation and the Physical Church-Turing Thesis. British Journal for Philosophy of Science 54, pp. 181-223.
     
54. Davies, E.B. (2001) Building Infinite Machines. British Journal for Philosophy of Science 52(4), pp. 671-682.
     
55. Davis, M. (1958) Computability and Unsolvability. New York: McGraw-Hill.
     
56. Deutsch, D. (1985) Quantum Theory, the Church-Turing Principle and the Universal Quantum Computer. Proc. Royal Soc., Series A 400, pp 97-117.
     
57. Doyle, J. (1982) What is Church's Thesis? An Outline. Laboratory for Computer Science, MIT.
     
58. Doyle, J. (2002) What is Church’s Thesis? An Outline. Minds and Machines 12, pp. 519–520.
     
59. Dreyfus, H.L. (1979) What Computers Can't Do: The Limits of Artificial Intelligence. New York, NY: Harper & Row, revised, ed.tion.
     
60. Dreyfus, H.L. (1992) What Computers Still Can't Do: A Critique of Artificial Reason. Cambridge, MA, USA: MIT Press.
     
61. Earman, J. (1995) Bangs, Crunches, Whimpers, and Shrieks - Singularities and Acausalities in Relativistic Spacetimes, Oxford: Oxford University Press.
     
62. Earman, J. & J.D. Norton (1993) Forever is a Day: Supertasks in Pitowsky and Malament-Hogarth Spacetimes. Philosophy of Science 60, pp. 22-42.
     
63. Earman, J. & J.D. Norton (1996) 'Infinite Pains: The Trouble with Supertasks' in: A. Morton and S.P. Stich, ed. Benacerraf and his Critics, Oxford: Blackwell.
     
64. Franklin, S. & M. Garzon (1991) 'Neural Computability' in: O. Omidvar (ed.) Progress in Neural Networks 1, Ablex.
     
65. Gams, M., Paprzycki, M. and Wu, X., eds. (1997) Mind versus Computer: Were Dreyfus and Winograd Right? Frontiers of Artificial Intelligence and Applications 43, Amsterdam: IOS Press.
     
66. Gams, M. (2002) The Turing Machine May Not Be the Universal Machine - A Reply to Dunlop. Minds and Machines 12, pp. 137–142.
     
67. Gandy, R. (1980) 'Church's Thesis and Principles for Mechanisms' in: J. Barwise, H.J. Kreisler and K. Kunen, ed. The Kleene Symposium, Amsterdam: North-Holland, pp. 123-148.
     
68. Gavaldà, R. & H.T. Siegelmann (1999) Discontinuities in Recurrent Neural Networks. Neural Computation 11 (3), pp. 715-745.
     
69. Garzon, M. & S. Franklin (1989) Neural Computability II. Proc. International Joint Conference on Neural Networks I, pp. 631-637.
     
70. Geroch, R. & J.B. Hartle (1986) Computability and Physical Theories. Foundations of Physics 16, pp. 533-550.
     
71. Gold, E.M. (1965) Limiting Recursion. J. Symbolic Logic 30, pp. 28-48.
     
72. Hamkins, J.D. (2002) Infinite Time Turing Machines. Minds and Machines 12, pp. 521–539.
     
73. Hartley, R. & H. Szu (1987) A Comparison of the Computational Power of Neural Network Models. Proc. IEEE Conf. on Neural Networks 1987, pp.17-22.
     
74. Harvey, I. and T. Bossomaier (1997) 'Time Out of Joint: Attractors in Asynchronous Random Boolean Networks' in: P. Husbands and I. Harvey, ed. Fourth European Conference on Artificial Life, Cambrdige, MA, USA: MIT Press.
     
75. Hasslacher, B. (1988) 'Beyond the Turing Machine' in: R.Herken (ed.), The Universal Turing Machine: A Half-Century Survey. Oxford: OUP (reprinted 1994; Berlin: Springer-Verlag)pp.387-402.
     
76. Hogarth, M.L. (1992) Does General Relativity Allow an Observer to View an Eternity in a Finite Time? Foundations of Physics Letters 5, pp. 173-81.
     
77. Hogarth, M.L. (1994) Non-Turing Computers and Non-Turing Computability, PSA 1, pp. 126-138. Available for download from the resources section of this site.
     
78. Hogarth, M.L. (1996) Predictability, Computability and Spacetime. (PhD Thesis). Available for download from the resources section of this site.
     
79. Hogarth, M.L. (2002) Deciding Arithmetic in Malament-Hogarth Spacetimes. Available for download from the resources section of this site.
     
80. Hogarth M. (2004) Deciding Arithmetic using SAD Computers. Brit. J. Phil. Sci. 55, pp. 681-691.
     
81. Israel, D. (2002) Reflections on Gödel's and Gandy's Reflections on Turing's Thesis. Minds and Machines 12, pp. 181-201.
     
82. Kampis, G. (1991) Self-Modifying Systems in Biology and Cognitive Science: A New Framework for Dyamics, Information and Complexity. Oxford: Pergamon.
     
83. Kampis, G. (1995) Computability, Self-Reference, and Self-Amendment. Communications and Cognition - Artificial Intelligence 12, pp. 91-110.
     
84. Karp, R.M. & R.J. Lipton (1982) 'Turing Machines that Take Advice' in: E. Engeler et al., ed. Logic and Algorithmic, Genève: L'Enseignement Mathématique.
     
85. Kieu, T. (2002, 7 March) Computing the noncomputable. Available for download from the resources section of this site, and at the Los Alamos Archive (http://xxx.lanl.gov/), arXiv:quant-ph/0203034.
     
86. Kieu, T.D. (2002) Quantum Hypercomputation. Minds and Machines 12, pp. 541–561.
     
87. Kilian J. & H.T. Siegelmann (1996) The Dynamic Universality of Sigmoidal Neural Networks. Information and Computation 128(1), pp. 48-56.
     
88. Kleene, S.C. (1967) Mathematical Logic New York: Wiley.
     
89. Komar, A. (1964) Undecidability of macroscopically distinguishable states in quantum field theory. Physical Review (second series) 133B, pp. 542-544.
     
90. Kreisel, G. (1965) 'Mathematical Logic' in: T.L. Saaty, ed., Lectures on Modern Mathematics, Vol. 3, New York: John Wiley.
     
91. Kreisel, G. (1967) 'Mathematical Logic: What has it done for the Philosophy of Mathematics?' in: R. Schoenmann, ed., Bertrand Russell: Philosopher of the Century, London: George Allen and Unwin.
     
92. Kreisel, G. (1970) 'Hilbert's Programme and the Search for Automatic Proof Procedures' in: M. Laudet et al., ed. Symposium on Automatic Demonstration, Lecture Notes in Mathematics 125. Berlin: Springer.
     
93. Kreisel, G. (1971) 'Some Reasons for Generalising Recursion Theory' in: R.O. Gandy and C.M.E. Yates, ed. Logic Colloquium '69. Amsterdam: North-Holland.
     
94. Kreisel, G. (1972) Which Number-Theoretic Problems can be Solved in Recursive Progressions on π₁¹-Paths through 0? J. Symbolic Logic 37, pp. 311-334.
     
95. Kreisel, G. (1974) A Notion of Mechanistic Theory. Synthese 29, pp.11-26.
     
96. Kreisel, G. (1982) Review of Pour-El and Richards. Journal of Symbolic Logic 47, pp. 900-902.
     
97. Kreisel, G. (1987) Church's Thesis and the Ideal of Formal Rigour. Notre Dame J. Formal Logic 28, pp. 499-519.
     
98. Krylov, S.M. (1986) Formal Technology and Universal Systems. Cybernetics Part 1(4), pp. 85-89 & Part 2(5), pp. 28-31.
     
99. Krylov, S.M. (1996) Formal Technology and Cognitive Processes. Int. J. General Systems 24, pp. 233-243.
     
100. Krylov, S.M. (1997) Formal Technology in Philosophy, Engineering, Bio-evolution and Sociology. Samara State Technical University.
      
101. Kugel, P. (1986) Thinking May Be More Than Computing. Cognition 32, pp. 137-198.
      
102. Kugel, P. (1990) Myhill's thesis: there's more than computing in musical thinking. Computer Music Journal 14(1), pp. 12-25.
      
103. Kugel, P. (2001) Can computers be genuinely intelligent? Available for download from the resources section of this site.
      
104. Kugel, P. (2002) Computing Machines Can’t Be Intelligent (...and Turing Said So). Minds and Machines 12, pp. 563–579.
      
105. I. Licata (2007) Effective Physical Processes and Active Information in Quantum Computing. Quantum Biosystems (ISSN 1970-223X) 1(1), pp. 51-65. Also available online at: arxiv.org/abs/0705.1173.
      
106. Lipshitz, L. & L.A. Rubel (1987) A Differentially Algebraic Replacement Theorem, and Analog Computability. Proc. Amer. Math. Soc. 99, pp. 367-372.
      
107. Lipton, R.J. (1995) DNA Solution of Hard Computational Problems. Science 268, pp. 542-545.
      
108. Lokhorst, G.J. (2000) Why I am not a Super-Turing Machine. Hypercomputation Workshop, University College London, 24 May 2000.
      
109. Maass, W. & P. Orponen (1997) On the Effect of Analog Noise in Discrete-Time Analog Computability. NeuroColt Technical Report Series, NC-TR-97-042.
      
110. Maass, W. & E.D. Sontag (1997) Analog Neural Nets with Gaussian or Other Common Noise Distributions cannot Recognise Arbitrary Regular Languages. NeuroColt Technical Report Series, NC-TR-97-043.
      
111. Maass, W. & E.D. Sontag (1999) Analog Neural Nets with Gaussian or Other Common Noise Distributions cannot Recognise Arbitrary Regular Languages. Neural Computation 11(3), pp. 771-782.
      
112. MacLennan, B.J. (1987) 'Technology-Independent Design of Neurocomputers: The Universal Field Computer' in: M. Caudill and C. Butler, ed., Proceedings of the IEEE First International Conference on Neural Networks, Vol 3, San Diego, CA: IEEE Press, pp. 39-49.
      
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114. MacLennan, B.J. (1990) Field Computation: A Theoretical Framework for Massively Parallel Analog Computation, Parts I-IV. Technical Report CS-90-100, Dept of Computer Science, University of Tennessee, Knoxville, USA. Also available online at http://www.cs.utk.edu/~mclennan/
      
115. MacLennan, B.J. (1993) Characteristics of Connectionist Knowledge Representation. Information Sciences 70, pp. 119-143. Also available online at http://www.cs.utk.edu/~mclennan/
      
116. MacLennan, B.J. (1993) 'Field Computation in the Brain' in: K. Pribram, ed., Rethinking Neural Networks: Quantum Fields and Biological Data, Hillsdale, NJ: Lawrence Erlbaum, pp. 199-232. Also available online at http://www.cs.utk.edu/~mclennan/
      
117. MacLennan, B.J. (1993) Grounding Analog Computers. Think 2, pp. 48-51. Also available online at http://www.cs.utk.edu/~mclennan/ and at http://cogprints.soton.ac.uk/abs/comp/199906003
      
118. MacLennan, B.J. (1994) 'Continuous Computation and the Emergence of the Discrete' in: K.H. Pribram, ed., Origins: Brain & Self-Organisation, Hillsdale, NJ: Lawrence Erlbaum, pp. 121-151. Also available online at http://www.cs.utk.edu/~mclennan/ and at http://cogprints.soton.ac.uk/abs/comp/199906001
      
119. MacLennan, B.J. (1994) 'Continuous Symbol Systems: The Logic of Connectionism' in: D.S. Levine, M. Aparicio IV, eds., Neural Networks for Knowledge Representation and Inference, Hillsdale, NJ: Lawrence Erlbaum, pp. 121-151. Also available online at http://www.cs.utk.edu/~mclennan/.
      
120. MacLennan, B.J. (1995) 'Continuous Formal Systems: A Unifying Model in Language and Cognition' in: Proc. IEEE Workshop on Architectures for Semiotic Modeling and Situation Analysis in Large Complex Systems, Monterey, CA, pp. 161-172. Also available online at http://www.cs.utk.edu/~mclennan/ and at http://cogprints.soton.ac.uk/abs/comp/199906002
      
121. MacLennan, B.J. (1997) 'Field Computation in Motor Control' in: P.G. Morasso and V. Sanguineti, eds., Self-Organization, Computational Maps and Motor Control, Amsterdam, The Netherlands: Elsevier, pp. 37-73. Also available online at http://www.cs.utk.edu/~mclennan/.
      
122. MacLennan, B.J. (1999) Field Computation in Natural and Artificial Intelligence. Information Sciences 119, pp. 73-89. Also available online at http://www.cs.utk.edu/~mclennan/.
      
123. MacLennan, B.J. (2001) Can Differential Equations Compute? Technical Report UT-CS-01-459, Dept of Computer Science, University of Tennessee, Knoxville, USA. Also available online at http://www.cs.utk.edu/~mclennan/.
      
124. MacLennan, B.J. (2003) Transcending Turing Computability. Minds and Machines 13(1), pp. 3-22.
      
125. Montague, R. (1962) 'Towards a GeneralTheory of Computability' in: B.Kazemier and D.Vuysje (eds.), Logic and Language. Reidel.
      
126. Mulhauser, G.R. (1998) Mind Out of Matter.
      
127. Ord, T. (2002) Hypercomputation: computing more than the Turing machine (Honours Thesis). Available for download from the resources section of this site.
      
128. Penrose, R. (1989) The Emperor's New Mind concerning Computers, Minds and the Laws of Physics. Oxford: Oxford University Press.
      
129. Penrose, R. (1990) Précis of The Emperor's New Mind: Concerning Computers, Minds and the Laws of Physics. Behavioural and Brain Sciences 13, pp. 643-655 and 692-705.
      
130. Penrose, R. (1994) Shadows of the Mind: A Search for the Missing Science of Consciousness. Oxford: Oxford University Press.
      
131. Piccinini, G. (2003) Alan Turing and the Mathematical Objection. Minds and Machines 13(1), pp. 23-48.
      
132. Pitowsky, I. (1990) The Physical Church Thesis and Physical Computational Complexity. Iyuun 39, pp.81-99.
      
133. Pour-El, M.B. (1974) Abstract Computability and its Relation to the General Purpose Analog Computer. Trans. Amer. Math. Soc. 199, pp. 1-28.
      
134. Pour-El, M.B. & J.I. Richards (1979) A Computable Ordinary Differential Equation Which Possesses No Computable Solution. Annals of Mathematical Logic 17, pp. 61-90.
      
135. Pour-El, M.B. & J.I. Richards (1981) The Wave Equation with Computable Initial Data such that its Unique Solution is not Computable. Advances in Mathematics 39, pp. 215-239.
      
136. Pour-El, M.B. & J.I. Richards (1989) Computability in Analysis and Physics. Berlin: Springer.
      
137. Putnam, H. (1960) 'Minds and Machines' in: S. Hook, ed., Dimensions of Mind. New York: New York University Press.
      
138. Putnam, H. (1965) Trial and Error Predicates and the Solution of a Problem of Mostowski. J. Symbolic Logic 30, pp. 49-57.
      
139. Putnam, H. (1992) Renewing Philosophy. Cambridge, MA, USA: Harvard University Press.
      
140. Rubel, L.A. (1985) The Brain as an Analog Computer. J. Theoretical Neurobiology 4, pp. 73-81.
      
141. Rubel, L.A. (1988) Some Mathematical Limitations of the General-Purpose Analog Computer. Advances in Applied Mathematics 9, pp. 22-34.
      
142. Rubel, L.A. (1989) Digital Simulation of Analog Computation and Church's Thesis. The Journal of Symbolic Logic 54, pp. 1011-1017.
      
143. Scarpellini, B. (1963) Zwei Unentscheitbare Probleme der Analysis. Zeitschrift für mathematische Logik undGrundlagen der Mathematik 9, pp. 265-289.
      
144. Scarpellini, B. (2003) Two Undecidable Problems of Analysis. Minds and Machines 13(1), pp. 49-77.
      
145. Scarpellini, B. (2003) Comments on 'Two Undecidable Problems of Analysis'. Minds and Machines 13(1), pp. 79-85.
      
146. Schweizer, P. (2002) Consciousness and Computation - A Reply to Dunlop. Minds and Machines 12, pp. 143–144.
      
147. Seligman, J. (2002) The Scope of Turing’s Analysis of Effective Procedures. Minds and Machines 12, pp. 203–220.
      
148. Shagrir, O. (1997) Two Dogmas of Computationalism. Minds and Machines 7, pp. 321-344.
      
149. Shagrir, O. (2002) Effective Computation by Humans and Machines. Minds and Machines 12, pp. 221-240.
      
150. Shagrir, O. & I. Pitowsky (2003) Physical Hypercomputation and the Church-Turing Thesis. Minds and Machines 13(1), pp. 87-101.
      
151. Siegelmann, H.T. (1995) Computation Beyond the Turing Limit. Science 268, pp. 545-548.
      
152. Siegelmann, H.T. (1996) Analog Computational Power, Science 271(19), January 1996, p. 373.
      
153. Siegelmann H.T. (1996) The Simple Dynamics of Super Turing Theories. Theoretical Computer Science 168 (2-part special issue on UMC), pp. 461-472.
      
154. Siegelmann, H.T. (1999) Neural Networks and Analog Computation: Beyond the Turing Limit.
      
155. Siegelmann, H.T. (1999) Stochastic Analog Networks and Computational Complexity. Journal of Complexity 15(4), pp. 451-475.
      
156. Siegelmann, H.T. (2003) Neural and Super-Turing Computing. Minds and Machines 13(1), pp. 103-114.
      
157. Siegelmann, H.T., A. Ben-Hur & S.Fishman (1999) Computational Complexity for Continuous Time Dynamics. Physical Review Letters 83(7), pp. 1463-1466.
      
158. Siegelmann, H.T. & S. Fishman (1998) Computation by Dynamical Systems. Physica D 120, pp. 214-235.
      
159. Siegelmann, H.T., B.G. Horne, & C.L.Giles (1997) Computational capabilities of recurrent NARX neural networks, IEEE Transactions on... [entry incomplete]
      
160. Siegelmann, H.T & M. Margenstern (1999) NineNeurons Suffice for Turing Universality. Neural Networks 12, pp. 593-600.
      
161. Siegelmann, H.T. & E.D. Sontag (1991) Turing Computability with Neural Networks. Applied Mathematics Letters 4(6), pp. 77-80.
      
162. Siegelmann, H.T. & E.D. Sontag (1992) On the Computational Power of Neural Nets, Proc. 5th Annual ACM Workshop on Computational Learning Theory, pp. 440-449.
      
163. Siegelmann, H.T. & E.D. Sontag (1994) Analog Computation via Neural Networks. Theoretical Computer Science 131, pp. 331-360.
      
164. Siegelmann, H.T. & E.D. Sontag (1995) Computational Power of Neural Networks. Journal of Computer System Sciences 50(1), pp. 132-150.
      
165. Smale, S. (1988) The Newtonian Contribution to our Understanding of the Computer. Queen's Quarterly 95, pp. 90-95.
      
166. Stannett, M. (1990) X-Machines and the Halting Problem: Building a Super-Turing Machine. Formal Aspects of Computing 2, pp. 331-341.
      
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