Nonparametric clustering using quantum mechanics

N Nasios; A G Bors

Nonparametric clustering using quantum mechanics

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper introduces a new nonparametric estimation approach that can be used for data that is not necessarily Gaussian distributed The proposed approach employs the Shrodinger partial differential equation. We assume that each data sample is associated with a quantum physics particle that has a radial field around its value. We consider a statistical estimation approach for finding the size of the influence field around each data sample. By implementing the Shrodinger equation we obtain a potential field that is assimilated with the data density. The regions of minima in the potential are determined by calculating the local Hessian on the potential hypersurface. The quantum clustering approach is applied for blind separation of signals and for segmenting SAR images of terrain based on surface normal orientation.

Original language	English
Title of host publication	2005 International Conference on Image Processing (ICIP), Vols 1-5
Place of Publication	NEW YORK
Publisher	IEEE
Pages	2581-2584
Number of pages	4
ISBN (Print)	0-7803-9134-9
Publication status	Published - 2005
Event	IEEE International Conference on Image Processing (ICIP 2005) - Genoa Duration: 11 Sept 2005 → 14 Sept 2005

Conference

Conference	IEEE International Conference on Image Processing (ICIP 2005)
City	Genoa
Period	11/09/05 → 14/09/05

Cite this

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title = "Nonparametric clustering using quantum mechanics",

abstract = "This paper introduces a new nonparametric estimation approach that can be used for data that is not necessarily Gaussian distributed The proposed approach employs the Shrodinger partial differential equation. We assume that each data sample is associated with a quantum physics particle that has a radial field around its value. We consider a statistical estimation approach for finding the size of the influence field around each data sample. By implementing the Shrodinger equation we obtain a potential field that is assimilated with the data density. The regions of minima in the potential are determined by calculating the local Hessian on the potential hypersurface. The quantum clustering approach is applied for blind separation of signals and for segmenting SAR images of terrain based on surface normal orientation.",

author = "N Nasios and Bors, {A G}",

year = "2005",

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booktitle = "2005 International Conference on Image Processing (ICIP), Vols 1-5",

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note = "IEEE International Conference on Image Processing (ICIP 2005) ; Conference date: 11-09-2005 Through 14-09-2005",

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T1 - Nonparametric clustering using quantum mechanics

AU - Nasios, N

AU - Bors, A G

PY - 2005

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N2 - This paper introduces a new nonparametric estimation approach that can be used for data that is not necessarily Gaussian distributed The proposed approach employs the Shrodinger partial differential equation. We assume that each data sample is associated with a quantum physics particle that has a radial field around its value. We consider a statistical estimation approach for finding the size of the influence field around each data sample. By implementing the Shrodinger equation we obtain a potential field that is assimilated with the data density. The regions of minima in the potential are determined by calculating the local Hessian on the potential hypersurface. The quantum clustering approach is applied for blind separation of signals and for segmenting SAR images of terrain based on surface normal orientation.

AB - This paper introduces a new nonparametric estimation approach that can be used for data that is not necessarily Gaussian distributed The proposed approach employs the Shrodinger partial differential equation. We assume that each data sample is associated with a quantum physics particle that has a radial field around its value. We consider a statistical estimation approach for finding the size of the influence field around each data sample. By implementing the Shrodinger equation we obtain a potential field that is assimilated with the data density. The regions of minima in the potential are determined by calculating the local Hessian on the potential hypersurface. The quantum clustering approach is applied for blind separation of signals and for segmenting SAR images of terrain based on surface normal orientation.

M3 - Conference contribution

SN - 0-7803-9134-9

SP - 2581

EP - 2584

BT - 2005 International Conference on Image Processing (ICIP), Vols 1-5

PB - IEEE

CY - NEW YORK

T2 - IEEE International Conference on Image Processing (ICIP 2005)

Y2 - 11 September 2005 through 14 September 2005

ER -