## References and models cited by this paper | ## References and models that cite this paper | |

Abbas HM, Fahmy MM (1994) Neural model for Karhunen-Loeve transform with application to adaptive image compression Amari S, Cichocki A (1998) Adaptive blind signal processing: Neural network approaches Amari SI (1977) Neural theory of association and concept-formation. Atick JJ, Redlich AN (1993) Convergent algorithm for sensory receptive field development Baldi PF, Hornik K (1995) Learning in linear neural networks: a survey. Bannour S, Azimi-Sadjadi MR (1995) Principal component extraction using recursive least squares learning. Barlow H (1989) Unsupervised learning Barlow H (2001) Redundancy reduction revisited. Barlow HB (1998) Guest editorial: Cerebral predictions Barlow HB, Foldiak P (1989) Adaptation and decorrelation in the cortex Bechtel W, Abrahamsen A (1993) Bell AJ, Sejnowski TJ (1995) An information-maximization approach to blind separation and blind deconvolution. Benvenuto N, Piazza F (1992) On the complex back-propagation algorithm Bertsekas DP (1996) Bingham E, Hyvärinen A (2000) A fast fixed-point algorithm for independent component analysis of complex valued signals. Celledoni E, Fiori S (2004) Neural learning by geometric integration of reduced rigid-body equations Chen T, Amari S (2001) Unified stabilization approach to principal and minor components extraction algorithms. Chen Y, Hou C (1992) High resolution adaptive bearing estimation using a complex-weighted neural network Chow TW, Fang Y (2001) Neural blind deconvolution of MIMO noisy channels Cichocki A, Amari S (2003) Costa S, Fiori S (2001) Image compression using principal component neural networks De_Castro MCF, De_Castro FCC, Amaral JN, Franco PRG (1998) A complex valued Hebbian learning algorithm Desodt G, Muller D (1990) Complex ICA applied to the separation of radar signals Diamantaras KI, Kung SY (1996) Douglas SC (2000) On gradient adaptation with unit-norm constraints Fiori S (2000) Blind separation of circularly distributed source signals by the neural extended APEX algorithm Fiori S (2001) A theory for learning by weight flow on Stiefel-Grassman manifold Fiori S (2002) A theory for learning based on rigid bodies dynamics. Fiori S (2003) Extended Hebbian learning for blind separation of complex-valued sources Fiori S (2003) A neural minor component analysis approach to robust constrained beamforming Fiori S (2003) Neural independent component analysis by 'maximum-mismatch' learning principle. Fiori S (2003) Fully-multiplicative orthogonal-group ICA neural algorithm Fiori S (2004) Fast fixed-point neural blind-deconvolution algorithm. Fiori S (2006) Fixed-point neural independent component analysis algorithms on the orthogonal group Fiori S, Faba A, Albini L, Cardelli E, Burrascano P (2003) Numerical modeling for the localization and the assessment of electromagnetic field sources Fiori S, Piazza F (2000) A general class of -APEX PCA neural algorithms Földiák P (1990) Forming sparse representations by local anti-Hebbian learning. Fyfe C, Macdonald D (2002) E-insensitive Hebbian learning Gao K, Ahmed MO, Swamy MNS (1994) A constrained anti-Hebbian learning algorithm for total least-squares estimation with applications to adaptive FIR and IIR filtering Georgiou GM, Koutsougeras C (1992) Complex-domain backpropagation Hairer E, Lubich C (2002) Hanna AI, Mandic DP (2003) A complex-valued nonlinear neural adaptive filter with a gradient adaptive amplitude of the activation function. Harpur GF (1997) Low entropy coding with unsupervised neural networks Haykin S (1989) Haykin S (1999) Hebb DO (1949) Helmke U, Moore JB (1993) Higuchi I, Eguchi S (2004) Robust principal component analysis with adaptive selection for tuning parameters Hyvärinen A (1999) Fast and robust fixed-point algorithms for independent component analysis. Hyvarinen A, Karunen J, Oja E (2001) Iserles A, Munthe-Kaas HZ, Norsett SP, Zanna A (2000) Lie-group methods Karhunen J, Joutsensalo J (1994) Representation and separation of signals using nonlinear PCA type learning Karhunen J, Joutsensalo J (1995) Generalizations of PCA, optimization problems, and neural networks Kates JM (1993) Superdirective arrays for hearing aids. Klemm R (1987) Adaptive airborne MTI: An auxiliary channel approach Kung SI, Diamantaras KI, Taur JS (1994) Adaptive principal component extraction (APEX) and applications Laheld B, Cardoso J-F (1994) Adaptive source separation with uniform performance. Levine DS, Brown VR, Shirey TV (1999) Liano K (1996) Robust error measure for supervised neural network learning with outliers. Lin Q, Amari SI, Chen T (1998) A unified algorithm for principal and minor components extraction. Linsker R (1992) Local synaptic rules suffice to maximize mutual information in a linear network Luo FL, Unbehauen R (1997) Mathew G, Reddy VU (1994) Development and analysis of a neural network approach to Pisarenko's harmonic retrieval method Mathis H, Douglas SC (2002) On the existence of universal nonlinearities for blind source separation Miao Y, Hua Y (1998) Fast subspace tracking and neural network learning by a novel information criterion Michaels RB, Upadhyaya BR (1999) A complex valued neural network with local learning laws Miller KD, MacKay DJC (1994) The role of constraints in Hebbian learning. Miyauchi M, Seki M, Watanabe A, Miyauchi A (1993) Interpretation of optical flow through complex neural network Muezzinoglu MK, Guzelis C, Zurada JM (2003) A new design method for the complex-valued multistate Hopfield associative memory. Nitta T (1997) An Extension of the Back-Propagation Algorithm to Complex Numbers. Nitta T (2000) An analysis of the fundamental structure of complex-valued neurons Nitta T (2004) Orthogonality of decision boundaries in complex-valued neural networks. Oja E (1982) A simplified neuron model as a principal component analyzer. Oja E (1989) Neural networks, principal components, and subspaces Oja E (1992) Principal components, minor components and linear neural networks Oja E (1994) Beyond PCA: Statistical expansions by nonlinear neural networks Oleary DP (1990) Robust regression computation using iteratively reweighted least squares. Palmieri F, Zhu J (1995) Self-association and Hebbian learning in linear neural networks. Pandey R (2001) Blind equalization and signal separation using neural networks Plumbley MD (1992) Efficient information transfer and anti-Hebbian neural networks. Plumbley MD (2003) Algorithms for non-negative independent component analysis Rubner J, Tavan P (1989) A self-organizing network for principal component analysis Sanger TD (1989) Optimal unsupervised learning in a single-layer linear feedforward neural networks Schmidt R (1986) Multiple emitter location and signal parameter estimation Shirazi MN, Peper F, Sawai H (1999) Principal component analysis by entropy-likelihood optimization Song W, Yilong L, Feng M (1998) An adaptive robust PCA neural network Spratling MW, Johnson MH (2002) Preintegration lateral inhibition enhances unsupervised learning. Sudjianto A, Hassoun MH (1995) Statistical basis of nonlinear Hebbian learning and application to clustering Thirion_Moreau N, Moreau E (2002) Generalized criterion for blind multivariate signal equalization Vegas JM, Zufiria PJ (2004) Generalized neural networks for spectral analysis: dynamics and Liapunov functions. Weingessel A, Hornik K (2000) Local PCA algorithms. Widrow B, Winter R (1988) Neural nets for adaptive filtering and adaptive pattern recognition Xu L (1992) Least mean square error reconstruction principle for self-organizing neural nets Xu L, Oja E, Suen CY (1992) Modified Hebbian learning for curve and surface fitting Xu L, Yuille AL (1995) Robust PCA by self-organizing rules based on statistical physics approach Yan WY, Helmke U, Moore JB (1994) Global analysis of Oja's flow for neural networks. Yang B (1995) Projection approximation subspace tracking Zufiria PJ (2002) On the discrete-time dynamics of the basic Hebbian neural network node. |