Diagnosis of plasma processing equipment using neural network recognition of wavelet-filtered impedance matching

Kim, Byungwhan; Kim, Sungmo

doi:10.1016/j.mee.2005.05.007

Cited by 14 publications

(1 citation statement)

References 12 publications

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“…9, the Wavelet transformation of the signal knowledge representation (from the acquired knowledge) is used to obtain its image knowledge representation from a processing based on analytical method. The used wavelet transformation is detailed in [23], [24], see also [25]. In both cases, the basis principle is to cut the obtained volume at a 'cut threshold', and then convert the amplitudes in grey levels in order to obtain an image [26].…”

Section: Image Knowledge Representationmentioning

confidence: 99%

Hybrid Intelligent Diagnosis Systems

Chohra

Kanaoui

Madani

2007

6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07)

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In this paper, the main objective is to give a methodology to design hybrid intelligent diagnosis systems for a large field of biomedicine and industrial applications. At first, a brief description on diagnosis tasks in such applications is presented. Second, diagnosis systems are presented. Third, the main steps of hybrid intelligent diagnosis systems are developed, for each step emphasizing problems and suggesting solutions able to ensure the design of hybrid intelligent diagnosis systems with a satisfactory reliability degree. In fact, the main steps discussed are knowledge representation, classification, classifier issued information fusion, and decision-making. Finally, a discussion is given with regard to the suggested methodology.

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Section: Image Knowledge Representationmentioning

confidence: 99%