Optimal unsupervised learning in a single-layer linear feedforward neural network

[1]  Jorge Herbert de Lira,et al.  Two-Dimensional Signal and Image Processing , 1989 .

[2]  Jae S. Lim,et al.  Two-Dimensional Signal and Image Processing , 1989 .

[3]  Geoffrey E. Hinton Connectionist Learning Procedures , 1989, Artif. Intell..

[4]  Kurt Hornik,et al.  Neural networks and principal component analysis: Learning from examples without local minima , 1989, Neural Networks.

[5]  Eduardo D. Sontag,et al.  Backpropagation Can Give Rise to Spurious Local Minima Even for Networks without Hidden Layers , 1989, Complex Syst..

[6]  R. Brockett,et al.  Dynamical systems that sort lists, diagonalize matrices and solve linear programming problems , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[7]  John G. Daugman,et al.  Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..

[8]  E. Adelson,et al.  Early vision and texture perception , 1988, Nature.

[9]  Tomaso Poggio,et al.  Computing texture boundaries from images , 1988, Nature.

[10]  Ralph Linsker,et al.  Self-organization in a perceptual network , 1988, Computer.

[11]  Teuvo Kohonen,et al.  The 'neural' phonetic typewriter , 1988, Computer.

[12]  Stephen Grossberg,et al.  The ART of adaptive pattern recognition by a self-organizing neural network , 1988, Computer.

[13]  D. O. Hebb,et al.  The organization of behavior , 1988 .

[14]  Terence D. Sanger,et al.  An Optimality Principle for Unsupervised Learning , 1988, NIPS.

[15]  Dana H. Ballard,et al.  Modular Learning in Neural Networks , 1987, AAAI.

[16]  H. Voorhees Finding Texture Boundaries in Images , 1987 .

[17]  R. Lippmann,et al.  An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.

[18]  Andrew S. Noetzel,et al.  Time-Sequential Self-Organization of Hierarchical Neural Networks , 1987, NIPS.

[19]  R Linsker,et al.  From basic network principles to neural architecture: emergence of orientation columns. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[20]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[21]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[22]  R. Linsker,et al.  From basic network principles to neural architecture , 1986 .

[23]  V. Brailovsky On an Incompletely Determined Model for Function Approximation by Experimental Data , 1985 .

[24]  J. Karhunen Recursive estimation of eigenvectors of correlation type matrices for signal processing applications , 1985 .

[25]  E. Oja,et al.  On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix , 1985 .

[26]  P. Lennie,et al.  Spatial frequency analysis in the visual system. , 1985, Annual review of neuroscience.

[27]  Juha Karhunen,et al.  Adaptive algorithms for estimating eigenvectors of correlation type matrices , 1984, ICASSP.

[28]  Daniel A. Pollen,et al.  Visual cortical neurons as localized spatial frequency filters , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[29]  D. Kazakos Optimal constrained representation and filtering of signals , 1983 .

[30]  V. Brailovsky ON THE PROBLEM OF FUNCTION APPROXIMATION BY SAMPLE SET PROCESSING FOR AN INCOMPLETELY DETERMINED MODEL , 1983 .

[31]  V. Brailovsky ON THE PROBLEM OF FUNCTION SYSTEM SELECTION FOR FUNCTION APPROXIMATION BASED ON THE USE OF A SAMPLE SET WITH DEFECTS , 1983 .

[32]  Erkki Oja,et al.  Subspace methods of pattern recognition , 1983 .

[33]  G. Golub Matrix computations , 1983 .

[34]  E. Bienenstock,et al.  Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[35]  T. Kohonen Self-organized formation of topographically correct feature maps , 1982 .

[36]  E. Oja Simplified neuron model as a principal component analyzer , 1982, Journal of mathematical biology.

[37]  D. Pollen,et al.  Phase relationships between adjacent simple cells in the visual cortex. , 1981, Science.

[38]  Smith,et al.  Introduction to Computing , 1979 .

[39]  D. Pollen,et al.  Relationship between spatial frequency selectivity and receptive field profile of simple cells. , 1979, The Journal of physiology.

[40]  Norman L. Owsley,et al.  Adaptive data orthogonalization , 1978, ICASSP.

[41]  Harold J. Kushner,et al.  wchastic. approximation methods for constrained and unconstrained systems , 1978 .

[42]  Lennart Ljung,et al.  Analysis of recursive stochastic algorithms , 1977 .

[43]  F. W. Kellaway,et al.  Advanced Engineering Mathematics , 1969, The Mathematical Gazette.

[44]  F. Downton Stochastic Approximation , 1969, Nature.

[45]  C. Enroth-Cugell,et al.  The contrast sensitivity of retinal ganglion cells of the cat , 1966, The Journal of physiology.

[46]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[47]  E. Ross The Organization of Will , 1916, American Journal of Sociology.