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Schemes for Bidirectional Modeling of Discrete Stationary Sources

机译:离散平稳源的双向建模方案

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摘要

We develop adaptive schemes for bidirectional modeling of unknown discrete stationary sources. These algorithms can be applied to statistical inference problems such as noncausal universal discrete denoising that exploit bidirectional dependencies. Efficient algorithms for constructing those models are developed and we compare their performance to that of the DUDE algorithm for universal discrete denoising
机译:我们开发了用于未知离散固定源的双向建模的自适应方案。这些算法可以应用于统计推断问题,例如利用双向依赖性的非因果通用离散降噪。开发了构建这些模型的有效算法,我们将其性能与用于通用离散降噪的DUDE算法的性能进行了比较

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