This paper presents an implementation of a digital filtering inspection system applied on a paper... more This paper presents an implementation of a digital filtering inspection system applied on a paper pulp sheet production process. The automation of the inspection phase is particularly critical during this process and its solution is highly complex. The system is based on neural network learning, allowing a compromise between resolution and processing speed. The experimental results demonstrating the use of this algorithm for the visual detection of defects in images obtained from a real factory environment are presented. These results show that the developed learning method generates filters that fulfil the required inspection standard.
Time series segmentation has many applications in several disciplines as neurology, cardiology, s... more Time series segmentation has many applications in several disciplines as neurology, cardiology, speech, geology and others. Many time series in this fields do not behave as stationary and the usual transformations to linearity cannot be used. This paper describes and evaluates different methods for segmenting non-stationary time series. We propose a modification of the algorithm in Lee et al. (2003) which is designed to searching for a unique change in the parameters of a time series, in order to find more than one change using an iterative procedure. We evaluate the performance of three approaches for segmenting time series: AutoSLEX (Ombao et al., 2002), AutoPARM (Davis et al., 2006) and the iterative cusum method mentioned above and referred as ICM. The evaluation of each methodology consists of two steps. First, we compute how many times each procedure fails in segmenting stationary processes properly. Second, we analyze the effect of different change patterns by counting how ma...
... Miguel Ángel Bermejo * ,; Daniel Peña,; Ismael Sánchez. ... Among the general tests, we inclu... more ... Miguel Ángel Bermejo * ,; Daniel Peña,; Ismael Sánchez. ... Among the general tests, we include in the evaluation the Tsay (1986) proposal, which is based on Tukey's one-degree-of-freedom test for non-additivity; the McLeod and Li (1983) proposal, which is a portmanteau test ...
This paper introduces a new class of robust estimates for ARMA models. They are M-estimates, but ... more This paper introduces a new class of robust estimates for ARMA models. They are M-estimates, but the residuals are computed so the effect of one outlier is limited to the period where it occurs. These estimates are closely related to those based on a robust filter, but they have two important advantages: they are consistent and the asymptotic theory is tractable. We perform a Monte Carlo where we show that these estimates compare favorably with respect to standard M-estimates and to estimates based on a diagnostic procedure.
This paper presents an implementation of a digital filtering inspection system applied on a paper... more This paper presents an implementation of a digital filtering inspection system applied on a paper pulp sheet production process. The automation of the inspection phase is particularly critical during this process and its solution is highly complex. The system is based on neural network learning, allowing a compromise between resolution and processing speed. The experimental results demonstrating the use of this algorithm for the visual detection of defects in images obtained from a real factory environment are presented. These results show that the developed learning method generates filters that fulfil the required inspection standard.
Time series segmentation has many applications in several disciplines as neurology, cardiology, s... more Time series segmentation has many applications in several disciplines as neurology, cardiology, speech, geology and others. Many time series in this fields do not behave as stationary and the usual transformations to linearity cannot be used. This paper describes and evaluates different methods for segmenting non-stationary time series. We propose a modification of the algorithm in Lee et al. (2003) which is designed to searching for a unique change in the parameters of a time series, in order to find more than one change using an iterative procedure. We evaluate the performance of three approaches for segmenting time series: AutoSLEX (Ombao et al., 2002), AutoPARM (Davis et al., 2006) and the iterative cusum method mentioned above and referred as ICM. The evaluation of each methodology consists of two steps. First, we compute how many times each procedure fails in segmenting stationary processes properly. Second, we analyze the effect of different change patterns by counting how ma...
... Miguel Ángel Bermejo * ,; Daniel Peña,; Ismael Sánchez. ... Among the general tests, we inclu... more ... Miguel Ángel Bermejo * ,; Daniel Peña,; Ismael Sánchez. ... Among the general tests, we include in the evaluation the Tsay (1986) proposal, which is based on Tukey's one-degree-of-freedom test for non-additivity; the McLeod and Li (1983) proposal, which is a portmanteau test ...
This paper introduces a new class of robust estimates for ARMA models. They are M-estimates, but ... more This paper introduces a new class of robust estimates for ARMA models. They are M-estimates, but the residuals are computed so the effect of one outlier is limited to the period where it occurs. These estimates are closely related to those based on a robust filter, but they have two important advantages: they are consistent and the asymptotic theory is tractable. We perform a Monte Carlo where we show that these estimates compare favorably with respect to standard M-estimates and to estimates based on a diagnostic procedure.
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Papers by Daniel Pena