Asymptotically optimal quantization schemes for Gaussian processes on Hilbert spaces

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Abstract

We describe quantization designs which lead to asymptotically and order optimal functional quantizers for Gaussian processes in a Hilbert space setting. Regular variation of the eigenvalues of the covariance operator plays a crucial role to achieve these rates. For the development of a constructive quantization scheme we rely on the knowledge of the eigenvectors of the covariance operator in order to transform the problem into a finite dimensional quantization problem of normal distributions. © EDP Sciences, SMAI, 2010.

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APA

Luschgy, H., Pagès, G., & Wilbertz, B. (2010). Asymptotically optimal quantization schemes for Gaussian processes on Hilbert spaces. ESAIM - Probability and Statistics, 14(2), 93–116. https://doi.org/10.1051/ps:2008026

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