Application to the Smoothing-Data Association Problem
An application of exponential smoothing methods to weather related data
... exponential smoothing method (SES) performed best for forecasting daily temperature time ...nential smoothing methods performed better than the seasonal naive method in forecasting daily temperature time ...
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Smoothing data association for target trajectory estimation in cluttered environments
... probabilistic data association (IPDA) tracking filters: one running forward in time (fIPDA) and the other running backward in time ...through data association to obtain the smoothing ...
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Fully Distributed Scalable Smoothing and Mapping with Robust Multi-robot Data Association
... the problem in which a robot r jointly estimates its trajectory X r and a map of landmarks L both within its local sensor range, as well as landmarks observed by neighboring ...this problem, where a robot ...
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Income Shocks, Coping Strategies, and Consumption Smoothing. An Application to Indonesian Data
... Various papers have shown the existence of an asset threshold below which households reduce consumption in order to preserve their stock of assets (asset smoothing). Other studies suggest that poor households ...
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Comparison of Methods for Smoothing Environmental Data with an Application to Particulate Matter PM10
... of smoothing lines (considered for each smoothing line separately) obtained using exponential smoothing, kernel regression, trend filtering and DWT adapts to the data better than using the ...
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Data Association Analysis In Simultaneous Localization And Mapping Problem
... the problem is known as the Simultaneous Localization and Mapping(SLAM)[1-3] which defines a state where a mobile robot must identify its location and its surroundings conditions ...the problem either by ...
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Overlapping Mixtures of Gaussian Processes for the data association problem
... instant data association decisions based on nearest-neighbor criteria or statistically more sophisticated approaches such as the Joint Prob- abilistic Data-Association Filter (JPDAF) [ 5 , 7 ] ...
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Topics in Application of Nonparametric Smoothing Splines
... correlated data, for example, Lin and Zhang (1999) use marginal quasi-likelihood method to choose the smoothing parameter in GAMM, and Zhang et ...the smoothing parameter in modeling Gaussian ...
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Classifiers Association for High Dimensional Problem: Application to Pedestrian Recognition
... the learning stage must be very huge and each sample can be described by a huge feature vector. We used the images dataset provided by Gavrila and Munder in (Munder & Gavrila, 2006). This base is subdivided into five ...
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Solution of the Problem of Smoothing of the Signals at the Preprocessing of Thermal Images
... 1 Introduction Image is a natural means of communication between man and machine in any processing, analysis and control systems. Therefore, one of the main problems of automation is the problem of visual ...
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Application of Clustering and Association Methods in Data Cleaning
... reference data and can give good ...the data examined and it is very likely that different data sets would need different values of the parameters to achieve a high ratio of correctly cleaned ...
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Data Smoothing Techniques: Historical and Modern
... Vernon Boys (1944) designed and constructed an integration machine. Instruments, such as a planimeter were used for testing what Sheppard called “closeness of fit.” A planimeter determines the area of a two-dimensional ...
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Exponential smoothing and non-negative data
... It is evident that only the purely multiplicative models of Class M can guarantee a sample space restricted to the positive half-line with suitable restrictions on the innovations. Class A contains the purely additive ...
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Approximating data with weighted smoothing splines
... some data from thin-film physics together with the default taut string approximation (Davies and Kovac ...The data were kindly supplied by ...the problem by using the weighted spline approximation ...
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Nonparametric Estimation: Smoothing and Data Visualization
... each r > 0. Since, by definition, exactly k observations fall in the interval [ x − d k ( x ) , x + d k ( x )] , an estimate of the density at x may be obtained by putting k = 2d k ( x ) n ˆf ( x ) . Note that while ...
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PRACTICAL GUIDE TO DATA SMOOTHING AND FILTERING
... Notes: 1. Recursive digital filters always have a time lag between input and output, non-recursive filters (where y is not fed back to the input side) can be made with zero-lag but do not allow a good approximation to a ...
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Data driven catchment classification: application to the pub problem
... the application of objective but merely statistical criteria and algorithms (PCA and CCA with SOM) revealed some limitations that may be significantly reduced by switching from data-driven to data- ...
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Non-linear exponential smoothing and positive data
... Class Y: Models with multiplicative errors and additive trend, and the model with multiplica- tive errors and additive seasonality but no trend: (M,A,∗), (M,A d ,∗) or (M,N,A), where ∗ denotes any admissible component (7 ...
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A new method for the data completion problem and application to obstacle detection
... Kohn-Vogelius functional. Then, in Section 4, we introduce the Tikhonov regulariza- tion term needed to numerically minimize the functional. The minimization of this regularized functional is considered by means of a ...
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Cladistic analysis of genotype data application to GAW15 Problem 3
... genetic data sets and, in particular, the move towards genome- wide studies, there is merit in considering analyses that gain computational efficiency by being more heuristic in ...15 Problem 3 simulated ...
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