A Kernel based multi-resolution time series analysis for screening deficiencies in paper production

• This paper is concerned with a multi-resolution tool for analysis of a time series aiming to detect abnormalities in various frequency regions. The task is treated as a kernel based novelty detection applied to a multi-level time series representation obtained from the discrete wavelet transform. Having a priori knowledge that the abnormalities manifest themselves in several frequency regions, a committee of detectors utilizing data dependent aggregation weights is build by combining outputs of detectors operating in those regions.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Keyword

Discrete transformation

Discrete time

Discrete wavelet

Time analysis

Kernel method

Medical screening

Screening

Neural network

TECHNOLOGY

TEKNIKVETENSKAP

Publication and Content Type

ref (subject category)

kon (subject category)