Foundations of recurrent neural networks
暂无分享,去创建一个
[1] S C Kleene,et al. Representation of Events in Nerve Nets and Finite Automata , 1951 .
[2] David E. Muller,et al. Complexity in Electronic Switching Circuits , 1956, IRE Trans. Electron. Comput..
[3] A. A. Mullin,et al. Principles of neurodynamics , 1962 .
[4] Marvin Minsky,et al. Perceptrons: An Introduction to Computational Geometry , 1969 .
[5] Ann Yasuhara,et al. Recursive function theory and logic , 1971, Computer science and applied mathematics.
[6] Saburo Muroga,et al. Threshold logic and its applications , 1971 .
[7] Larry J. Stockmeyer,et al. A characterization of the power of vector machines , 1974, STOC '74.
[8] Eduardo D. Sontag,et al. On certain questions of rationality and decidability , 1975 .
[9] Arto Salomaa,et al. Automata-Theoretic Aspects of Formal Power Series , 1978, Texts and Monographs in Computer Science.
[10] David S. Johnson,et al. Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .
[11] Eduardo D. Sontag,et al. Realization Theory of Discrete-Time Nonlinear Systems: Part I - The Bounded Case , 1979 .
[12] Jeffrey D. Ullman,et al. Introduction to Automata Theory, Languages and Computation , 1979 .
[13] George William Cherry. Pascal programming structures: An introduction to systematic programming , 1980 .
[14] J J Hopfield,et al. Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.
[15] A. Yao. Separating the polynomial-time hierarchy by oracles , 1985 .
[16] B. Dickinson,et al. The complexity of analog computation , 1986 .
[17] J. Håstad. Computational limitations of small-depth circuits , 1987 .
[18] R. Lippmann,et al. An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.
[19] J. R. Brown,et al. Artificial neural network on a SIMD architecture , 1988, Proceedings., 2nd Symposium on the Frontiers of Massively Parallel Computation.
[20] Jean Berstel,et al. Rational series and their languages , 1988, EATCS monographs on theoretical computer science.
[21] Eduardo Sontag. Controllability is harder to decide than accessibility , 1988 .
[22] Eduardo D. Sontag,et al. Backpropagation separates when perceptrons do , 1989, International 1989 Joint Conference on Neural Networks.
[23] David Haussler,et al. What Size Net Gives Valid Generalization? , 1989, Neural Computation.
[24] Ken-ichi Funahashi,et al. On the approximate realization of continuous mappings by neural networks , 1989, Neural Networks.
[25] S. Smale,et al. On a theory of computation and complexity over the real numbers; np-completeness , 1989 .
[26] George Cybenko,et al. Approximation by superpositions of a sigmoidal function , 1989, Math. Control. Signals Syst..
[27] S. M. Carroll,et al. Construction of neural nets using the radon transform , 1989, International 1989 Joint Conference on Neural Networks.
[28] Ronald J. Williams,et al. A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.
[29] W S McCulloch,et al. A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.
[30] Kurt Hornik,et al. Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks , 1990, Neural Networks.
[31] H. Stowell. The emperor's new mind R. Penrose, Oxford University Press, New York (1989) 466 pp. $24.95 , 1990, Neuroscience.
[32] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[33] J. Stephen Judd,et al. Neural network design and the complexity of learning , 1990, Neural network modeling and connectionism.
[34] Halbert White,et al. Approximating and learning unknown mappings using multilayer feedforward networks with bounded weights , 1990, 1990 IJCNN International Joint Conference on Neural Networks.
[35] Richard M. Karp,et al. Parallel Algorithms for Shared-Memory Machines , 1991, Handbook of Theoretical Computer Science, Volume A: Algorithms and Complexity.
[36] Eduardo D. Sontag,et al. Mathematical Control Theory: Deterministic Finite Dimensional Systems , 1990 .
[37] P. Boas. Machine models and simulations , 1991 .
[38] Hava T. Siegelmann,et al. The allocation of documents in multiprocessor information retrieval systems: an application of genetic algorithms , 1991, Conference Proceedings 1991 IEEE International Conference on Systems, Man, and Cybernetics.
[39] Hava T. Siegelmann,et al. Integrating Implicit Answers with Object-Oriented Queries , 1991, VLDB.
[40] Timothy X. Brown,et al. Competitive neural architecture for hardware solution to the assignment problem , 1991, Neural Networks.
[41] Eduardo D. Sontag,et al. Feedback Stabilization Using Two-Hidden-Layer Nets , 1991, 1991 American Control Conference.
[42] Roy Batruni,et al. A multilayer neural network with piecewise-linear structure and back-propagation learning , 1991, IEEE Trans. Neural Networks.
[43] Eduardo Sontag,et al. Turing computability with neural nets , 1991 .
[44] Thomas A. Henzinger,et al. Temporal proof methodologies for real-time systems , 1991, POPL '91.
[45] Y. C. Lee,et al. Turing equivalence of neural networks with second order connection weights , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.
[46] Georg Schnitger,et al. On the computational power of sigmoid versus Boolean threshold circuits , 1991, [1991] Proceedings 32nd Annual Symposium of Foundations of Computer Science.
[47] Kurt Hornik,et al. Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.
[48] B. MacLennan. Continuous Symbol Systems: The Logic of Connectionism , 1991 .
[49] Michael B. Matthews,et al. On the uniform approximation of nonlinear discrete-time fading-memory systems using neural network models , 1992 .
[50] Ronald L. Rivest,et al. Training a 3-node neural network is NP-complete , 1988, COLT '88.
[51] José L. Balcázar,et al. Characterizations of Logarithmic Advice Complexity Classes , 1992, IFIP Congress.
[52] C. Lee Giles,et al. Learning and Extracting Finite State Automata with Second-Order Recurrent Neural Networks , 1992, Neural Computation.
[53] Georg Schnitger,et al. The Power of Approximation: A Comparison of Activation Functions , 1992, NIPS.
[54] Eduardo D. Sontag,et al. Feedforward Nets for Interpolation and Classification , 1992, J. Comput. Syst. Sci..
[55] Eduardo D. Sontag,et al. NEURAL NETS AS SYSTEMS MODELS AND CONTROLLERS , 1992 .
[56] Héctor J. Sussmann,et al. Uniqueness of the weights for minimal feedforward nets with a given input-output map , 1992, Neural Networks.
[57] Solving combinatorial optimization problems by gradient flows , 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.
[58] Eduardo D. Sontag,et al. Rate of approximation results motivated by robust neural network learning , 1993, COLT '93.
[59] L. Motus. Time concepts in real-time software , 1993 .
[60] Eduardo D. Sontag,et al. UNIQUENESS OF WEIGHTS FOR NEURAL NETWORKS , 1993 .
[61] Aaron D. Wyner,et al. A Universal Turing Machine with Two Internal States , 1993 .
[62] Hava T. Siegelmann,et al. On the power of sigmoid neural networks , 1993, COLT '93.
[63] Hava T. Siegelmann,et al. Document Allocation In Multiprocessor Information Retrieval Systems , 1993, Advanced Database Systems.
[64] Allan Pinkus,et al. Multilayer Feedforward Networks with a Non-Polynomial Activation Function Can Approximate Any Function , 1991, Neural Networks.
[65] Wolfgang Maass,et al. Bounds for the computational power and learning complexity of analog neural nets , 1993, SIAM J. Comput..
[66] Eduardo D. Sontag,et al. Finiteness results for sigmoidal “neural” networks , 1993, STOC.
[67] Hava T. Siegelmann,et al. Some structural complexity aspects of neural computation , 1993, [1993] Proceedings of the Eigth Annual Structure in Complexity Theory Conference.
[68] Hava T. Siegelmann,et al. Analog computation via neural networks , 1993, [1993] The 2nd Israel Symposium on Theory and Computing Systems.
[69] Hava T. Siegelmann,et al. On the Computational Power of Neural Nets , 1995, J. Comput. Syst. Sci..