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Original Article

Quadratic forms in natural images

Pages 765-788 | Received 05 Dec 2002, Accepted 12 Aug 2003, Published online: 09 Jul 2009

References

  • Adelson E H, Bergen J R. Spatiotemporal energy models for the perception of motion. J. Opt. Soc. Am. A 1985; 2: 284–99
  • Bartsch H, Obermayer K. Second-order statistics of natural images. Neurocomputing 2003; 52–54: 467–72
  • Bell A J, Sejnowski T J. The ‘independent components’ of natural scenes are edge filters. Vis. Res. 1997; 37: 3327–38
  • Belouchrani A, Abed-Meraim K, Cardoso J-F, Moulines E. A blind source separation technique using second-order statistics. IEEE Trans. Signal Process. 1997; 45: 434–44
  • Berkes P, Wiskott L. Slow feature analysis yields a rich repertoire of complex-cell properties. 2003, Preprint CogPrints 2804 http://cogprints.ecs.soton.ac.uk
  • De Valois R L, Yund E W, Hepler N. The orientation and direction selectivity of cells in macaque visual cortex. Vis. Res. 1982; 22: 531–44
  • Einhäuser W, Kayser C, König P, Körding K P. Learning the invariance properties of complex cells from their responses to natural stimuli. Eur. J. Neurosci. 2002; 15: 475–86
  • Hurri J, Hyvärinen A. Simple-cell-like receptive fields maximize temporal coherence in natural video. Neural Comput. 2003a; 15: 663–91
  • Hurri J, Hyvärinen A. Temporal and spatiotemporal coherence in simple-cell responses: a generative model of natural image sequences. Network: Comput. Neural Syst. 2003b; 14: 527–51
  • Hyvärinen A. Blind source separation by nonstationarity of variance: a cumulant-based approach. IEEE Trans. Neural Netw. 2001a; 12: 1471–4
  • Hyvärinen A. Complexity pursuit: separating interesting components from time series. Neural Comput. 2001b; 13: 883–98
  • Hyvärinen A, Hoyer P. Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces. Neural Comput. 2000; 12: 1705–20
  • Kayser C, Einhäuser W, Dümmer O, König P, Körding K. Extracting slow subspaces from natural videos leads to complex cells. Artificial Neural Networks, ICANN 2001, G Doffner, H Bischof, K Hornik. Springer, Berlin 2001
  • Morrone M C, Burr D C, Maffei L. Functional implications of cross-orientation inhibition of cortical visual cells: I. Neurophysiological evidence. Proc. R. Soc. B 1982; 216: 335–54
  • Olshaseun A, Field J. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature 1996; 381: 607–9
  • Papoulis A. Probability, Random Variables, and Stochastic Processes. WCB/McGraw-Hill, New York 1991
  • Schwartz O, Simoncelli E P. Natural signal statistics and sensory gain control. Nature Neurosci. 2001; 4: 819–25
  • van Hateren J H, Ruderman D L. Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortex. Proc. R. Soc. B 1998; 265: 2315–20
  • Wiskott L, Sejnowski T. Slow feature analysis: unsupervised learning of invariances. Neural Comput. 2002; 14: 715–70
  • Zetzsche C, Röhrbein F. Nonlinear and extra-classical receptive field properties and the statistics of natural scenes. Network: Comput. Neural Syst. 2001; 12: 331–50

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