Found 147 results
Author Title [ Year(Asc)]
Barkai E, Hansel D, Sompolinsky H.  1992.  Broken symmetries in multilayered perceptrons. Physical Review. A. 45:4146–4161.PDF icon PhysRevA.45.4146.pdf (1.01 MB)
Golomb D, Hansel D, Shraiman B, Sompolinsky H.  1992.  Clustering in globally coupled phase oscillators. Physical Review. A. 45:3516–3530.PDF icon PhysRevA.45.3516.pdf (745.69 KB)
Tsodyks M., Sompolinsky H.  1992.  Processing of Sensory Information by a Network of Oscillators with Memory.. International Journal of Neural Systems 3, 51..
Seung HS, Opper M.A., Sompolinsky H.  1992.  Query by Committee.. in Proceedings of the Fifth Annual Workshop on Computational Learning Theory, Warmuth M.K. and Valiant L.G., editors. (Kaufmann, San Mateo, CA), p. 287..
Aranson I, Golomb D, Sompolinsky H.  1992.  Spatial coherence and temporal chaos in macroscopic systems with asymmetrical couplings. Physical Review Letters. 68:3495–3498.PDF icon PhysRevLett.68.3495.pdf (148.66 KB)
Seung HS, Sompolinsky H, Tishby N.  1992.  Statistical mechanics of learning from examples. Physical Review. A. 45:6056–6091.PDF icon PhysRevA.45.6056.pdf (2.3 MB)
Hansel D, Sompolinsky H.  1992.  Synchronization and computation in a chaotic neural network. Physical Review Letters. 68:718–721.PDF icon PhysRevLett.68.718.pdf (281.2 KB)
Sompolinsky H, Golomb D, Golomb D.  1991.  Cooperative dynamics in visual processing. Physical Review. A. 43:6990–7011.PDF icon PhysRevA.43.6990.pdf (1.01 MB)
Sompolinsky H, , .  1991.  Phase Coherence and Computation in a Neural Network of Coupled Oscillators. Non-Linear Dynamics and Neural Networks, Schuster H.G and Singer W, Eds. (VCH, Weinheim, 1991), pp. 113-140..
Kleinfeld D, Chiel HJ, Sompolinsky H.  1991.  Small Nervous Systems and Neural Network Models. Non-Linear Dynamics and Neural Networks, Schuster H.G and Singer W, Eds. (VCH, Weinheim, 1991), pp. 77-109.. PDF icon kleinfeld_small_nervous_systems_neural_net_1990.pdf (1.96 MB)
Sompolinsky H, Golomb D, Kleinfeld D.  1990.  Global processing of visual stimuli in a neural network of coupled oscillators. Proceedings of the National Academy of Sciences of the United States of America. 87:7200–7204.
Hansel D, Sompolinsky H.  1990.  Learning from Examples in a Single-Layer Neural Network.. Europhysics Letters 11, 687..
Sompolinsky H, Tishby N, S SH.  1990.  Learning from examples in large neural networks. Physical Review Letters. 65:1683–1686.PDF icon PhysRevLett.65.1683.pdf (346.2 KB)
Sompolinsky H, Tishby N.  1990.  Learning in a Two-Layer Neural Network of Edge Detectors.. Europhysics Letters 13, 567.. PDF icon 0295-5075_13_6_016.pdf (453 KB)
Barkai E, Kanter I, Sompolinsky H.  1990.  Properties of sparsely connected excitatory neural networks. Physical Review. A. 41:590–597.PDF icon PhysRevA.41.590.pdf (391.21 KB)
Golomb D, Rubin N, Sompolinsky H.  1990.  Willshaw model: Associative memory with sparse coding and low firing rates. Physical Review. A. 41:1843–1854.PDF icon PhysRevA.41.1843.pdf (627.63 KB)
Kleinfeld D, Sompolinsky H.  1989.  Associative Network Models for Central Pattern Generators. Methods in Neuronal Modeling: From Synapse to Networks, Koch C and Segev I, Eds., Ch. 7 (MIT Press, Cambridge, MA 1989). pp. 195-246.. PDF icon kleinfeld_assoc_network_models_cpg_1988.pdf (5.85 MB)
Rubin N, Sompolinsky H.  1989.  Neural Networks with Low Local Firing Rates. Europhysics Letters 10, 465.. PDF icon 0295-5075_10_5_013.pdf (454.61 KB)
Yacoby ER, Wolfus Y, Yeshurun Y, Felner I, Sompolinsky H.  1989.  Scaling of the irreversible magnetization curves of YBaCuO. Physica C: Superconductivity. 162–164(1)PDF icon 7physica_c_i_1989.pdf (120.1 KB)
Wolfus Y, Yeshurun Y, Felner I, Sompolinsky H.  1989.  Scaling properties of the irreversible magnetization curves of high-temperature superconductors. Physical Review. B, Condensed Matter. 40:2701–2703.PDF icon PhysRevB.40.2701.pdf (153.48 KB)