Order Estimation of Superimposed Nonlinear Complex Cisoid Model Using Adaptively Penalizing Likelihood Rule: Consistency Results
| Autor: | Sharmishtha Mitra, Anupreet Porwal |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Gaussian Estimator 020206 networking & telecommunications Information Criteria 02 engineering and technology Function (mathematics) Machine learning computer.software_genre Exponential function Nonlinear system symbols.namesake Bayesian information criterion Consistency (statistics) 0202 electrical engineering electronic engineering information engineering symbols Applied mathematics 020201 artificial intelligence & image processing Artificial intelligence business computer Astrophysics::Galaxy Astrophysics Mathematics |
| Zdroj: | DEStech Transactions on Engineering and Technology Research. |
| ISSN: | 2475-885X |
| DOI: | 10.12783/dtetr/amma2017/13387 |
| Popis: | Recently a novel approach of model order selection based on penalizing adaptively the likelihood (PAL) function was introduced in [1]. In this paper, we use the PAL method for order estimation of complex valued nonlinear exponential (cisoid) model and study its asymptotic statistical properties. We investigate the asymptotic statistical properties for the 1-dimensional cisoid model under the assumption of circularly symmetric gaussian error distribution and establish that the PAL estimator is consistent. We also present simulation examples to compare the performance of PAL rule with the commonly used information criteria based rules. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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