Neural computation

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  Año 2005, Vol. 17, Número 9

  • The Cocktail Party Problem

    Zhe Chen, Simon Haykin

    págs. 1875-1902

    

  • Edgeworth Approximation of Multivariate Differential Entropy

    Marc M. Van Hulle

    págs. 1903-1910

    

  • Perfect Fault Tolerance of the n-k-n Network

    Elko B. Tchernev, Dhananjay S. Phatak, Rory G. Mulvaney

    págs. 1911-1920

    

  • On the Slow Convergence of EM and VBEM in Low-Noise Linear Models

    Kaare Brandt Petersen, Lars Kai Hansen, Ole Winther

    págs. 1921-1926

    

  • Analyzing Functional Connectivity Using a Network Likelihood Model of Ensemble Neural Spiking Activity

    Matthew A. Wilson, Murat Okatan, Emery N. Brown

    págs. 1927-1961

    

  • Data-Robust Tight Lower Bounds to the Information Carried by Spike Times of a Neuronal Population

    Stefano Panzeri, R.S. Petersen, A. Thiele, M.P. Young, G. Pola

    págs. 1962-2005

    

  • Fluctuation-Dissipation Theorem and Models of Learning

    Ilya Nemenman

    págs. 2006-2033

    

  • Correlated Firing in a Feedforward Network with Mexican-Hat-Type Connectivity

    Kazuyuki Aihara, Kosuke Hamaguchi, Michiko Yamana, Masato Okada

    págs. 2034-2059

    

  • Supervised Learning in a Recurrent Network of Rate-Model Neurons Exhibiting Frequency Adaptation

    Emmanuel Guigon, Pierre A. Fortier, Yves Burnod

    págs. 2060-2076

    

  • Learning Bounds for Kernel Regression Using Effective Data Dimensionality

    Tong Zhang

    págs. 2077-2098