Generalized Hebbian Algorithm

Known as: GHA, Sanger's rule 
The Generalized Hebbian Algorithm (GHA), also known in the literature as Sanger's rule, is a linear feedforward neural network model for unsupervised… (More)
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2017
2017
Inertial measurement units (IMUs) enable human motion measurement in any environment, which can be useful for human robot… (More)
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2017
2017
In this manuscript neural networks architecture is used for image compression. We analyzed the PCA technique with the help of… (More)
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2016
2016
By applying Generalized Hebbian Algorithm (GHA), this work deals with the problem of on-line process monitoring for a… (More)
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2015
2015
A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike… (More)
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2012
2012
This paper presents a novel hardware architecture for principal component analysis. The architecture is based on the Generalized… (More)
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2008
2008
The principal component analysis (PCA) is a data mining methodology to express multivariate data comprehensively. The PCA reduces… (More)
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2006
2006
In this paper we perform image compression and face recognition using principal component analysis (PCA) and the generalized… (More)
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Highly Cited
2006
Highly Cited
2006
An algorithm based on the Generalized Hebbian Algorithm is described that allows the singular value decomposition of a dataset to… (More)
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2005
2005
The Generalized Hebbian Algorithm is shown to be equivalent to Latent Semantic Analysis, and applicable to a range of LSAstyle… (More)
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2003
2003
Principal component extraction is an efficient statistical tool that is applied to feature extraction, data compression, and… (More)
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