1,768 research outputs found
Filtered derivative with p-value method for multiple change-points detection
This paper deals with off-line detection of change points for time series of
independent observations, when the number of change points is unknown. We
propose a sequential analysis like method with linear time and memory
complexity. Our method is based at first step, on Filtered Derivative method
which detects the right change points but also false ones. We improve Filtered
Derivative method by adding a second step in which we compute the p-values
associated to each potential change points. Then we eliminate as false alarms
the points which have p-value smaller than a given critical level. Next, our
method is compared with the Penalized Least Square Criterion procedure on
simulated data sets. Eventually, we apply Filtered Derivative with p-Value
method to segmentation of heartbeat time series
Off-line detection of multiple change points with the Filtered Derivative with p-Value method
This paper deals with off-line detection of change points for time series of
independent observations, when the number of change points is unknown. We
propose a sequential analysis like method with linear time and memory
complexity. Our method is based at first step, on Filtered Derivative method
which detects the right change points but also false ones. We improve Filtered
Derivative method by adding a second step in which we compute the p-values
associated to each potential change points. Then we eliminate as false alarms
the points which have p-value smaller than a given critical level. Next, our
method is compared with the Penalized Least Square Criterion procedure on
simulated data sets. Eventually, we apply Filtered Derivative with p-Value
method to segmentation of heartbeat time series, and detection of change points
in the average daily volume of financial time series
Fast change point analysis on the Hurst index of piecewise fractional Brownian motion
In this presentation, we introduce a new method for change point analysis on
the Hurst index for a piecewise fractional Brownian motion. We first set the
model and the statistical problem. The proposed method is a transposition of
the FDpV (Filtered Derivative with p-value) method introduced for the detection
of change points on the mean in Bertrand et al. (2011) to the case of changes
on the Hurst index. The underlying statistics of the FDpV technology is a new
statistic estimator for Hurst index, so-called Increment Bernoulli Statistic
(IBS). Both FDpV and IBS are methods with linear time and memory complexity,
with respect to the size of the series. Thus the resulting method for change
point analysis on Hurst index reaches also a linear complexity
Detection of Change--Points in the Spectral Density. With Applications to ECG Data
We propose a new method for estimating the change-points of heart rate in the
orthosympathetic and parasympathetic bands, based on the wavelet transform in
the complex domain and the study of the change-points in the moments of the
modulus of these wavelet transforms. We observe change-points in the
distribution for both bands.Comment: proceeding of the workshop 'Fouille de donn\'ees temporelles et
analyse de flux de donn\'ees' EGC'2009, january 27, Strasbourg, Franc
SPIRAL2 accelerator construction progress
TH2A02 - ISBN 878-3-95450-122-9International audienceThe installation of the SPIRAL2 superconducting accelerator at GANIL is almost started. All the major components have been tested in the various partner laboratories, and the building construction is now well engaged. The management of the interfaces between the process and the buildings is a strategic point in an underground accelerator, with strong space constraints. This paper describes the performances of the various components
Wind Farm Power Forecasting
Forecasting annual wind power
production is useful for the energy industry. Until recently,
attention has only been paid to the mean annual wind power energy
and statistical uncertainties on this forecasting. Recently,
Bensoussan et al. (2012) have pointed that the annual wind
power produced by one wind turbine is a Gaussian random variable
under a reasonable set of assumptions. Moreover, they can derive
both mean and quantiles of annual wind power produced by one wind
turbine. The novelty of this work is the obtainment of similar
results for estimating the annual wind farm power production.
Eventually, we study the relationship between the power production
for each turbine of the farm in order to avoid interaction between
them
Fast change point analysis on the Hurst index of piecewise fractional Brownian motion
International audienceIn this presentation, we introduce a new method for change point analysis on the Hurst index for a piecewise fractional Brownian motion. We first set the model and the statistical problem. The proposed method is a transposition of the FDpV (Filtered Derivative with p-value) method introduced for the detection of change points on the mean in Bertrand et al. (2011) to the case of changes on the Hurst index. The underlying statistics of the FDpV technology is a new statistic estimator for Hurst index, so-called Increment Bernoulli Statistic (IBS). Both FDpV and IBS are methods with linear time and memory complexity, with respect to the size of the series. Thus the resulting method for change point analysis on Hurst index reaches also a linear complexity
Beam dynamics studies in SPIRAL II LINAC
ACCInternational audienceThe proposed LINAG driver for the SPIRAL 2 project aims to accelerate a 5-mA D+ beam up to 20 A.MeV and 1-mA beam for q/A=1/3 up to 14.5 A.MeV. It is acontinuous wave regime (cw), designed for maximum efficiency in the transmission of intense beams. It consists of an injector (two ECR sources + a Radio Frequency Quadrupole) followed by a superconducting section based on an array of independently phased cavities. This paper presents beams dynamics studies associated to the LINAG driver. End-to-end simulations (low-energy beam lines, RFQ, medium-energy beam line, SC linac) are shown
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