Results 301 to 310 of about 4,837,596 (345)

Unsupervised Classification of Multivariate Time Series Using VPCA and Fuzzy Clustering With Spatial Weighted Matrix Distance

IEEE Transactions on Cybernetics, 2020
Due to high dimensionality and multiple variables, unsupervised classification of multivariate time series (MTS) involves more challenging problems than those of univariate ones.
Hong He, Yonghong Tan
semanticscholar   +1 more source

Preconditioners for distance matrix algorithms

Journal of Computational Chemistry, 1994
AbstractA recent gradient algorithm in nonlinear optimization uses a novel idea that avoids line searches. This so‐called spectral gradient algorithm works well when the spectrum of the Hessian of the function to be minimized has a small range or is clustered. In this article, we find a general preconditioning method for this algorithm.
W. Glunt, T. L. Hayden, M. Raydan
openaire   +1 more source

Robust Sensor Localization Based on Euclidean Distance Matrix

IEEE International Geoscience and Remote Sensing Symposium, 2018
In remote sensing systems, exact knowledge of the sensor locations is critical for generating focused images. In order to accurately locate misplaced or perturbed sensors from their received signal data, we proposed a robust sensor localization method ...
Dehong Liu, H. Mansour, P. Boufounos, U. Kamilov   +3 more
semanticscholar   +1 more source

Distance Matrix Completion by Numerical Optimization

Computational Optimization and Applications, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Nearest Neighbour Distance Matrix Classification

2010
A distance based classification is one of the popular methods for classifying instances using a point-to-point distance based on the nearest neighbour or k-NEAREST NEIGHBOUR (k-NN). The representation of distance measure can be one of the various measures available (e.g.
Sainin, Mohd Shamrie, Alfred, Rayner
openaire   +2 more sources

Euclidean distance matrix completion problems

Optimization Methods and Software, 2012
Our experiments show that the method easily solves the artificial problems introduced by More and Wu. It also solves the 12 much more difficult protein fragment problems introduced by Hendrickson, and the six larger protein problems introduced by Grooms, Lewis and Trosset.
Haw-ren Fang, Dianne P. O'Leary
openaire   +1 more source

Topological energy of the distance matrix

Communications in nonlinear science & numerical simulation, 2021
Chun-Xiao Nie
semanticscholar   +1 more source

[Reconstruction of genetic distance matrix].

Genetika, 1990
A method for reconstruction of genetic distances' matrix, based on linear combination of physical distances' matrices among populations and mean sizes of the population matrices is proposed. The analogue of genetic distances' matrix obtained correlates with the matrix at the level 0.59.
G I, El'chinova, A A, Revazov, M Iu, Kadoshnikova   +2 more
openaire   +1 more source

Distance-Based Logistic Matrix Factorization

Neural Computation
Abstract Matrix factorization is a central paradigm in matrix completion and collaborative filtering. Low-rank factorizations have been extremely successful in reconstructing and generalizing high-dimensional data in a wide variety of machine learning problems from drug-target discovery to music recommendations.
Anoop Praturu, Tatyana O. Sharpee
openaire   +1 more source

Distance/Distance Matrixes

Journal of Chemical Information and Computer Sciences, 1994
Milan Randic, Alexander F. Kleiner, Luz M. De Alba   +2 more
openaire   +1 more source