Nowadays distance measures techniques have been quickly developed and widely used to the real application. The main objective of this thesis is to make a brief introduction of different distance measures methods, especially spike-time distance and its application to point pattern prototypes and Multi-Dimensional Scaling (MDS) methods. Meantime, R programming packages for spike-time distance, prototype and Multi-Dimensional Scaling have also been introduced in order to make these methods more practical and convenient to the real world. And, their packages are used to a real dataset as an application
Abstract Distance metric forms the basis of pattern classification, as almost all classifiers depend...
International audienceThe dbmss package for R provides an easy-to-use toolbox to characterize the sp...
© 2017 Elsevier B.V. The analysis of clustering and correlation between points on a linear network, ...
This work discusses computational problems related to the implementation of Victor and Purpura’s spi...
This paper presents a collection of dissimilarity measures to describe and then classify spatial poi...
Much like in other modeling disciplines does the distance metric used (a measure for dissimilarity) ...
We study local similarity based distance measures for point-patterns. Such measures can be used for ...
The basic concepts of distance based classification are introduced in terms of clear-cut example sys...
A histogram of a set with respect a measurement represents the frequency of quantified values of tha...
The distance between a pair of spike trains, quantifying the differences be-tween them, can be measu...
Measuring the similarity (or distance) between trajectories of moving objects is a common procedure ...
Measuring the similarity (or distance) between trajectories of moving objects is a common procedure ...
This work focuses on similarity measures that can be applied on different driving behaviors. Also m...
The dbmss package for R provides an easy-to-use toolbox to characterize the spatial structure of poi...
Integration of rich sensor technologies with everyday applications, such as gesture recognition and ...
Abstract Distance metric forms the basis of pattern classification, as almost all classifiers depend...
International audienceThe dbmss package for R provides an easy-to-use toolbox to characterize the sp...
© 2017 Elsevier B.V. The analysis of clustering and correlation between points on a linear network, ...
This work discusses computational problems related to the implementation of Victor and Purpura’s spi...
This paper presents a collection of dissimilarity measures to describe and then classify spatial poi...
Much like in other modeling disciplines does the distance metric used (a measure for dissimilarity) ...
We study local similarity based distance measures for point-patterns. Such measures can be used for ...
The basic concepts of distance based classification are introduced in terms of clear-cut example sys...
A histogram of a set with respect a measurement represents the frequency of quantified values of tha...
The distance between a pair of spike trains, quantifying the differences be-tween them, can be measu...
Measuring the similarity (or distance) between trajectories of moving objects is a common procedure ...
Measuring the similarity (or distance) between trajectories of moving objects is a common procedure ...
This work focuses on similarity measures that can be applied on different driving behaviors. Also m...
The dbmss package for R provides an easy-to-use toolbox to characterize the spatial structure of poi...
Integration of rich sensor technologies with everyday applications, such as gesture recognition and ...
Abstract Distance metric forms the basis of pattern classification, as almost all classifiers depend...
International audienceThe dbmss package for R provides an easy-to-use toolbox to characterize the sp...
© 2017 Elsevier B.V. The analysis of clustering and correlation between points on a linear network, ...