Link

Publication

 

2000

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Secure and Linear Cryptosystems Using Error Correcting Codes
I. Kanter E. Kanter and L. Ein-Dor
Europhys. Lett. 51, 244

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Robust Chaos Generation by a Perceptron
A. Priel and I. Kanter
Europhys. Lett. 51, 230

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Dynamics of Interacting Neural Networks
W. Kinzel, R. Metzler and I. Kanter
J. Phys. A 33 L141

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Learning and Generation of Long Range Correlated Sequences
A. Priel and I. Kanter
Phys. Rev. E 62, 1617

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Finite Size Effects and Error-Free Communication in Gaussian Channel
I. Kanter and D. Saad
J. Phys. A 33, 1675

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Cascading Parity-Check Error-Correcting Codes
I. Kanter and D. Saad
Phys. Rev. E 61 2137

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Interacting Neural Networks
W. Kinzel, R. Metzler and I. Kanter
Phys. Rev. E 62, 2555

 

1999

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Statistical Properties of Contact Maps
M. Vendruscolo, B. Subramanian, I. Kanter, E. Domany and J. Lebowitz
Phys. Rev. E 59, 977

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Confidence in the Prediction by Neural Networks
L. Ein-Dor and I. Kanter
Phys. Rev. E 60 799

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Error Correcting Codes That Nearly Saturate Shannon's Bound
I. Kanter and D. Saad
Phys. Rev. Lett. 83, 2660

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Long Term Properties of Time Series Generated by a  Perceptron with Various Transfer Functions
A. Priel and I. Kanter
Phys. Rev. E 59 , 3668

 

1998

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Analytical Study of the Interplay Between Architecture and Predictability
A. Priel, I. Kanter and D. Kessler
In Neural Information Processing Systems, 10, 15
Eds. by S. A. Solla M. I. Jordan and M. Kearens (MIT Press).

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Learnability of Periodic Activation Functions: General Results
M. Rosen-Zvi, M Biehl and I. Kanter
Phys. Rev. E 58, 3606

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Time Series Generation by Multi-Layer Networks
L. Ein-Dor and I. Kanter
Phys. Rev. E 57, 6564

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Noisy Time Series Generation by Feed-Forward Networks
A. Priel, I. Kanter and D. Kessler
Journal of Physics A 31, 1189

 

1997

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Storage Capacity of Correlated Perceptrons
D. Malzahn, A. Engel and I. Kanter
Phys. Rev. E 55, 7369

 

1996

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Emergence of Chaos in Asymmetric Networks
I. Kanter
Phys. Rev. Lett. 77, 4844

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Cluster Dynamics for Randomly Frustrated Systems with Finite Connectivity
N. Persky, I. Kanter and S. Solomon
Phys. Rev. E 53, 1212

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Mean-Field Behavior of Cluster Dynamics
N. Persky, R. Ben-Av, I. Kanter and E. Domany
Phys. Rev. E 54, 2351

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Training a Perceptron by a Bit Sequence: Storage Capacity
M. Schroder, W. Kinzel and I. Kanter
J. Phys. A 29, 7965

 

1995

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The Bit-Generator and Time Series Prediction
E. Eisenstein, I. Kanter, D. Kessler and W. Kinzel
Neural Networks: The Statistical Mechanics Perspective, 131-140, Eds: J. Oh, C.
Kwon and S. Cho (World Scientific Publishing Co.)

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Markov Processes: Linguistics, Zipf's Law and Long-Range Correlations
I. Kanter and D. Kessler
Phys. Rev. Lett. 74, 4559

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Generation and Prediction of Time Series by a Neural Network
E. Eisenstein, I. Kanter, D. Kessler and W. Kinzel
Phys. Rev. Lett. 74, 6

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On the Equivalence of Boolean Two-Layered Perceptrons with Binary Weights
M. Blatt, E. Domany and I. Kanter
Int. J. Neural Sys. 6, 225

 

1994

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Computational Capabilities of Restricted Two Layered Perceptrons
A. Priel, M. Blatt, T. Grossman, E. Domany and I. Kanter
Phys. Rev. E 50, 577

 

1993

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Do Classical Spin Systems with the Same Metastable  States Have Identical Hamiltonians?
I. Kanter and R. Gotesdyner
Phys. Rev. Lett. 72, 2678

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The Binary Perceptron and General Aspects of  Non-Self-Averaged Quantities
I. Kanter and M. Shvartser
Physica A 200, 670

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Generalization Performance of Complex Adaptive Tasks
E. Eisenstein and I. Kanter
Phys. Rev. Lett. 70, 3667

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Numerical Study of Back propagation Learning Algorithms for multilayer networks
E. Eisenstein and I. Kanter
Europhys. Lett. 21, 501

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Computational Capability of Classical and Quantum Spin Systems
I. Kanter and E. Eisenstein
J. Phys. A 26, L201

 

1992

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Hidden Information in Hamiltonian Systems with Discrete Weights
I. Kanter
Phys. Rev. A 45, 6051

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Information Theory of a Multilayer Neural Network with Discrete Weights
I. Kanter
Europhys. Lett. 17, 181