References
- Atick J J. Could information theory provide an ecological theory of sensory processing?. Network: Comput. Neural Syst. 1992; 3: 213–51
- Atick J J, Redlich A N. Towards a theory of early visual processing. Neural Comput. 1990; 2: 308–20
- Atick J J, Redlich A N. Convergent algorithm for sensory receptive field development. Neural Comput. 1993; 5: 45–60
- Barlow H B. Unsupervised learning. Neural Comput. 1989; 1: 295–311
- Bell A J, Sejnowski T J. An information maximization approach to blind separation and blind deconvolution. Neural Comput. 1995a; 7: 1129–59
- Bell A J, Sejnowski T J (1995b) Fast blind separation based on information theory, in. Proc. Int. Symp. on Nonlinear Theory and Applications, NOLTA, Las Vegas, December, 1995. IEICE, 1: 43–7
- Comon P. Independent component analysis, a new concept?. Signal Process. 1994; 36: 287–314
- Daugman J G. Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. J. Opt. Soc. Am. A 1985; 2 7: 1160–9
- Field D J. Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A 1987; 4: 12, 2370–93
- Field D J. What is the goal of sensory coding?. Neural Comput. 1994; 6: 559–601
- Foldiak P. Forming sparse representations by local anti-Hebbian learning. Biol. Cybern. 1990; 64: 165–70
- Goodall M C. Performance of stochastic net. Nature 1960; 185: 557–8
- Harpur G F, Prager R W. Development of low entropy coding in a recurrent network. Network: Comput. Neural Syst. 1996; 7: 272–84
- Haykin S. Blind Deconvolution, S Haykin. Prentice-Hall, Englewood Cliffs, NJ 1994
- Intrator N. Feature extraction using an unsupervised neural network. Neural Comput. 1992; 4: 98–107
- Jutten C, Herault J. Blind separation of sources, part I: an adaptive algorithm based on neuromimetic architecture. Signal Processing 1991; 24: 1–10
- Karhunen J, Wang L, Jousensalo J (1995) Neural estimation of basis vectors in independent component analysis. Proc. Int. Conf. on Artificial Neural Networks ICANN, Paris, 1995. Springer, Berlin
- Linsker R. Self-organization in a perceptual network. Computer 1988; 21: 105–17
- Miller K D. Correlation-based models of neural development. Neuroscience and Connectionist Theory, M Gluck, D Rumelhart. Erlbaum, Hillsdale, NJ 1988; 267–353
- Nadal J-P, Parga N. Non-linear neurons in the low noise limit: a factorial code maximizes information transfer. Network: Comput. Neural Syst. 1994; 5: 565–81
- Oja E. Neural networks, principal components and linear neural networks. Neural Networks 1989; 5: 927–35
- Olshausen B A, Field D J. Natural image statistics and efficient coding. Network: Comput. Neural Syst. 1996; 7: 333–9
- Sanger T D. Optimal unsupervised learning in a single-layer network. Neural Networks 1989; 2: 459–73