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Volume 23, Issue 9

September 2011

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ISSN 0899-7667

EISSN 1530-888X

In this Issue

Article
Letters

Article

Finding the Event Structure of Neuronal Spike Trains

J. Vincent Toups, Jean-Marc Fellous, Peter J. Thomas, Terrence J. Sejnowski, Paul H. Tiesinga

Neural Computation (2011) 23 (9): 2169–2208.

Abstract

View articletitled, Finding the Event Structure of Neuronal Spike Trains

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Letters

The Dependence of Spike Field Coherence on Expected Intensity

Kyle Q. Lepage, Mark A. Kramer, Uri T. Eden

Neural Computation (2011) 23 (9): 2209–2241.

Abstract

View articletitled, The Dependence of Spike Field Coherence on Expected Intensity

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Active Data Collection for Efficient Estimation and Comparison of Nonlinear Neural Models

Christopher DiMattina, Kechen Zhang

Neural Computation (2011) 23 (9): 2242–2288.

Abstract

View articletitled, Active Data Collection for Efficient Estimation and Comparison of Nonlinear Neural Models

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Invariant Object Recognition and Pose Estimation with Slow Feature Analysis

Mathias Franzius, Niko Wilbert, Laurenz Wiskott

Neural Computation (2011) 23 (9): 2289–2323.

Abstract

View articletitled, Invariant Object Recognition and Pose Estimation with Slow Feature Analysis

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A Differential Model of the Complex Cell

Miles Hansard, Radu Horaud

Neural Computation (2011) 23 (9): 2324–2357.

Abstract

View articletitled, A Differential Model of the Complex Cell

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Principles and Typical Computational Limitations of Sparse Speaker Separation Based on Deterministic Speech Features

Albert Kern, Ruedi Stoop

Neural Computation (2011) 23 (9): 2358–2389.

Abstract

View articletitled, Principles and Typical Computational Limitations of Sparse Speaker Separation Based on Deterministic Speech Features

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Kernels for Longitudinal Data with Variable Sequence Length and Sampling Intervals

Zhengdong Lu, Todd K. Leen, Jeffrey Kaye

Neural Computation (2011) 23 (9): 2390–2420.

Abstract

View articletitled, Kernels for Longitudinal Data with Variable Sequence Length and Sampling Intervals

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Algorithms for Nonnegative Matrix Factorization with the β-Divergence

Cédric Févotte, Jérôme Idier

Neural Computation (2011) 23 (9): 2421–2456.

Abstract

View articletitled, Algorithms for Nonnegative Matrix Factorization with the β-Divergence

Article

Finding the Event Structure of Neuronal Spike Trains

Letters

The Dependence of Spike Field Coherence on Expected Intensity

Active Data Collection for Efficient Estimation and Comparison of Nonlinear Neural Models

Invariant Object Recognition and Pose Estimation with Slow Feature Analysis

A Differential Model of the Complex Cell

Principles and Typical Computational Limitations of Sparse Speaker Separation Based on Deterministic Speech Features

Kernels for Longitudinal Data with Variable Sequence Length and Sampling Intervals

Algorithms for Nonnegative Matrix Factorization with the β-Divergence

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