Convergence Proof for Unsteady Classification Model with Data Fluctuations

Peng Wu

doi:10.4028/www.scientific.net/AMM.513-517.2297

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Convergence Proof for Unsteady Classification...

Convergence Proof for Unsteady Classification Model with Data Fluctuations

Abstract:

Convergence of unsteady classification model with data fluctuations has strong application value. This paper models the mathematical problem to verify the feasibility and finite convergence of unsteady classification model with data fluctuations, and verifies the feasibility and limited convergence of the model by convex optimization KKT equivalent conditions from different perspectives. Experiments validate the three real data sets collected, and results show that the proposed model is feasible and finite convergence.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

2297-2300

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.2297

Citation:

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Online since:

February 2014

Authors:

Peng Wu*

Keywords:

Classification Model, Convergence, Non-Stationary Fluctuations

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