Searching for "Oja learning rule." – sorted by Relevance.
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A Fully-Differential CMOS Implementation of Oja's Learning Rule in a Dual-Synapse Neuron
- A Fully-Differential CMOS Implementation of Oja’s Learning Rule in a Dual-Synapse Neuron
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A VLSI-Design of the Minimum Entropy Neuron
- with the Oja learning rule (Oja 1982, Sanger 1989); the same as in other asymmetric networks with additional
- Cited by 2 (2 self) – Add To MetaCart
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On-Line Learning with Time-Correlated Patterns
- and the Kohonen learning rule. Simulations with Oja's rule illustrate the theoretical results. PACS: 87.10., 02
- Cited by 7 (5 self) – Add To MetaCart
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Principal Subspace Analysis For Incomplete Image Data In One Learning Epoch
- of the covariance matrix E[xx T ]: The well-known Oja's learning rule [2] allows to find the principal vector: 1w
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Neuronal Regulation and Hebbian Learning
- learning rule discussed above and the BCM model. Using the linear perceptron V = P i w i x i , Oja
- Cited by 1 (0 self) – Add To MetaCart
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ORIGINAL CONTRIB UTION Optimal Unsupervised Learning in a Single-Layer Linear Feedforward Neural
- , we will often refer to (10) as "the Oja learning rule.") Oja claims that (10) can be ap- proximated
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Exploring the Time-Domain Solutions to Oja's Equations
- neuron following Oja’s learning rule in an environment modeling the classical visual cortical plasticity
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Stochastic Dynamics of Learning with Momentum in Neural Networks
- = j=(1 \Gamma ff). Simulations with the nonlinear Oja learning rule confirm the theoretical results
- Cited by 6 (4 self) – Add To MetaCart
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Hierarchical Neural Network for Robust PCA Computation of Complex Valued Signals
- of the functions ae 2 (e) = 1 2 e 2 , yielding 9(e) = e, simplifies to the well-known Oja's learning rule
- Cited by 1 (1 self) – Add To MetaCart
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Learning Processes in Neural Networks
- can be calculated. We compare our analytical results with simulations for the Oja learning rule [9
- Cited by 30 (7 self) – Add To MetaCart

