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Principal component analysis

Known as: Principle components analysis, Principle Component Analysis, Probabilistic principal component analysis 
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
In the area of computer vision and machine intelligence, image recognition is a prominent field. There have been several… 
2008
2008
Computer vision and image recognition research have a great interest in dimensionality reduction techniques. Generally these… 
2008
2007
2007
Abstract : Geometric harmonics provides a framework for taking data in high-dimensional measurement spaces and embedding them in… 
2006
2006
Stochastic dynamic programming models are attractive for multireservoir control problems because they allow non‐linear features… 
2002
2002
We develop a new signal modeling method, entropy-constrained adaptive PCA, that has the flexibility to accurately model the… 
1995
1995
Student display of regular physical activity has been presented as a principal component of the definition of a physically… 
1986
1986
Multiple components of magnetization were isolated in the natural remanent magnetiza- tion of samples of the Upper Devonian… 
Highly Cited
1986
Highly Cited
1986
The concept of fast KL transform coding introduced earlier [7], [8] for first-order Markov processes and certain random fields… 
Highly Cited
1981
Highly Cited
1981
A class of stable algorithms for adapting infinite impulse response (IIR) digital filters based on the concepts of nonlinear…