Local independent component analysis applied to highly segmented detectors

Filho, Eduardo Furtado Simas; Seixas, J. M.; Calôba, L. P.

doi:10.1109/iscas.2008.4542090

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Cited by 3 publications

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“…The main indeterminacy of the Local ICA method is the appropriated number of clusters for each problem. Feature extraction procedures based on NLICA have recently been proposed in [52,72,84,85] for the ATLAS detector [86] triggering system. The aim was to increase the particle discrimination efficiency of the online filtering task, which is performed in harsh conditions.…”

Section: 6-general Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Nonlinear Independent Component Analysis: Theoretical Review And Applications

Filho¹,

Seixas²

2007

L&NLM

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-This paper reviews the Nonlinear Independent Components Analysis and its applications to blind source separation. An overview of the main statistical principles that guide the search for the independent components is formulated. The uniqueness of solution and some algorithms for estimating the nonlinear independent components are discussed. Experimental results using a synthetic database are used for performance comparison. A practical application in experimental high-energy physics is also presented.

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Section: 6-general Discussionmentioning

confidence: 99%

“…Low P F is also essential for the classifier design, as the huge background noise has to be rejected, as much as possible, to allow offline data analysis on clean data. In [84], Local ICA (as described in Section 3.4) was applied to the ring formatted signals. The dataset was split into four groups using SOM for clustering.…”

Section: 6-general Discussionmentioning

confidence: 99%