Cpt |
K.I. Harrington and H.T. Siegelmann |
Adaptive Multi-modal Sensors |
50 Years of Artificial Intelligence, eds. M. Lungarella, F. Iida, J. Bongard, R. Pfeifer |
2007 |
164-173 |
pdf |
Cpt |
Bhaskar DasGupta, Derong Liu and Hava Siegelmann |
Neural Networks |
Handbook on Approximation Algorithms and Metaheuristics, ed. Teofilo F. Gonzalez, Chapman & Hall/CRC (Computer & Information Science Series, ed. Sartaj Sahni) |
2007 |
22.1-22.14 |
- |
Cpt |
H. T. Siegelmann |
Neural Computing |
New Trends in Computer Science, ed. Gheroge Paul |
2003 |
- |
- |
Cpt |
H.T. Siegelmann |
Neural Automata and Computational Complexity |
in Handbook of Brain Theory and Neural Networks, ed. Michael A. Arbib |
2002 |
- |
- |
Cpt |
H.T. Siegelmann |
Universal Computation and Super-Turing Capabilities |
Field Guide to Dynamical Recurrent Networks, eds. S.C. Kremer and J.F. Kolen, IEEE Press |
2000 |
- |
- |
Cpt |
H.T. Siegelmann |
Finite vs. Infinite Descriptive Length in Neural Networks and the Associated Computational Complexity |
Finite vs. Infinite: Contributions to an Eternal Dilemma, eds. C. Calude and Gh. Paun, Springer Verlag |
2000 |
- |
- |
Cpt |
H.T. Siegelmann |
Neural Automata and Computational Complexity |
Handbook of Brain Theory and Neural Networks, ed. Michael A. Arbib |
2000 |
- |
- |
Cpt |
H. Lipson and H.T. Siegelmann |
High Order Eigentensors as Symbolic Rules in Competitive Learning |
Hybrid Neural Symbolic Integration, eds. S. Wermter and R. Sun, Springer |
1999 |
- |
- |
Cpt |
H.T. Siegelmann |
Neural Dynamics with Stochasticity |
Adaptive Processing of Sequences and Data Structures, eds. C.L. Giles and M. Gori, Springer |
1998 |
346-369 |
pdf |
Cpt |
H.T. Siegelmann |
Computability with Neural Networks |
Lectures in Applied Mathematics, Vol. 32, J. Reneger, eds. M. Shub, and S. Smale, American Mathematical Society |
1996 |
733-747 |
- |
Cpt |
H.T. Siegelmann |
Neural Automata |
Shape, Structures and Pattern Recognition, eds. D. Dori and F. Bruckstein, World Scientific |
1995 |
- |
- |
Cpt |
H.T. Siegelmann |
Towards a Neural Programming Language |
Shape, Structures and Pattern Recognition, eds. D. Dori and F. Bruckstein, World Scientific |
1995 |
- |
- |
Cpt |
H.T. Siegelmann |
Recurrent Neural Networks |
The 1000th Volume of Lecture Notes in Computer Science: Computer Science Today, ed. Jan Van Leeuwen, Springer Verlag |
1995 |
29-45 |
- |
Cpt |
H.T. Siegelmann |
Welcoming the Super-Turing theories |
Lecture Notes in Computer Science, Vol. 1012, eds. M. Bartosek, J. Staudek, J. Wiedermann, Springer Verlag |
1995 |
83-94 |
- |
Cpt |
H.T. Siegelmann, B.G. Horne, and C.L. Giles |
What NARX Networks Can Compute |
Lecture Notes in Computer Science: Theory and Practice of Informatics, Vol. 1012, eds. M. Bartosek, J. Staudek, J. Wiedermann, Springer Verlag |
1995 |
95-102 |
- |
Cpt |
B. DasGupta, H.T. Siegelmann, and E. Sontag |
On the Intractability of Loading Neural Networks |
Theoretical Advances in Neural Computation and Learning, eds. V.P. Roychowdhury, K.Y. Siu, and A. Orlitsky, Kluwer Academic Publishers |
1994 |
- |
- |
Cpt |
H.T. Siegelmann |
On the Computational Power of Probabilistic and Faulty Neural Networks |
Lecture Notes in Computer Science, Vol. 820: Automata, Languages and Programming, eds. S. Abiteboul and E. Shamir, Springer Verlag |
1994 |
20-34 |
- |
Cpt |
H.T. Siegelmann and O. Frieder |
Document Allocation in Multiprocessor Information Retrieval Systems |
Lecture Notes in Computer Science, Vol. 759: Advanced Database Concepts and Research Issues, eds. N.R. Adam and B. Bhargava, Springer Verlag |
1993 |
289-310 |
- |