Adaptive multiple minor directions extraction in parallel using a PCA neural network

DOI10.1016/j.tcs.2010.07.021zbMath1208.68184OpenAlexW2026566337MaRDI QIDQ606986

Kok Kiong Tan, Zhang Yi, Jian Cheng Lv, Su-Nan Huang

Publication date: 19 November 2010

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2010.07.021

zbMATH Keywords

global convergenceprincipal component analysisdeterministic discrete time methodminor component analysis

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Unnamed Item
• Adaptive algorithms for first principal eigenvector computation
• Global convergence of Oja's PCA learning algorithm with a non-zero-approaching adaptive learning rate
• On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix
• Sequential extraction of minor components
• Generalized neural networks for spectral analysis: dynamics and Liapunov functions
• Analysis of recursive stochastic algorithms
• On Stability of Neural Networks by a Lyapunov Functional-Based Approach
• Global convergence of Lotka-Volterra recurrent neural networks with delays

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