At the edge of chaos: Real-time computations and self-organized criticality in recurrent neural networks

Advances in Neural Information Processing Systems

Volumn , Issue , 2005, Pages

  Natschläger, Thomas ^a   Bertschinger, Nils ^b   Legenstein, Robert ^c  

^a Software Competence Center Hagenberg   (Austria)

^b MAX PLANCK INSTITUTE FOR MATHEMATICS IN THE SCIENCES   (Germany)

^c GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

CRITICALITY (NUCLEAR FISSION); RECURRENT NEURAL NETWORKS; THRESHOLD LOGIC;

CHAOTIC DYNAMICS; COMPLEX COMPUTATION; COMPLEXITY MEASURES; COMPUTATIONAL CAPABILITY; DYNAMICAL PROPERTIES; RANDOMLY CONNECTED NETWORKS; REAL-TIME COMPUTATIONS; SELF-ORGANIZED CRITICALITY;

COMPLEX NETWORKS;

EID: 84898977685     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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4. N. Bertschinger and T. Natschlager. Real-time computation at the edge of chaos in recurrent neural networks. Neural Computation, 16(7):1413-1436, 2004.
5. W. Maass, T. Natschlager, and H. Markram. Real-time computing without stable states: A new framework for neural computation based on perturbations. Neural Computation, 14(11), 2002.
6. H. Jaeger and H. Haas. Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication. Science, 304(5667):78-80, 2004.
7. S. Bornholdt and T. Rohl. Self-organized critical neural networks. Physical Review E, 67:066118, 2003.
8. N. Bertschinger and T. Natschlager. Supplementary information to the meanfield theory for randomly connected recurrent networks of threshold gates, 2004. http://www.igi.tugraz.at/tnatschl/edge-of-chaos/mean-field-supplement.pdf.