Source Coding for a Wiener Process

We develop a novel source coding strategy for sampling and monitoring of a Wiener process. For the encoding process, we employ a four level ``quantization'' scheme, which employs monotone function thresholds as opposed to fixed constant thresholds. Leveraging the hitting times of the Wiener process with these thresholds, we devise a sampling and encoding strategy which does not incur any quantization errors. We give analytical expressions for the mean squared error (MSE) and find the optimal source code lengths to minimize the MSE under this monotone function threshold scheme, subject to a sampling rate constraint.

Publication Details

Journal
ArXiv.org
Published
2025-04-02
Primary Topic
Advanced Data Compression Techniques
Type
article
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article

Source Coding for a Wiener Process

ArXiv.org
Advanced Data Compression Techniques
article

Source Coding for a Wiener Process

article en

Abstract

We develop a novel source coding strategy for sampling and monitoring of a Wiener process. For the encoding process, we employ a four level ``quantization'' scheme, which employs monotone function thresholds as opposed to fixed constant thresholds. Leveraging the hitting times of the Wiener process with these thresholds, we devise a sampling and encoding strategy which does not incur any quantization errors. We give analytical expressions for the mean squared error (MSE) and find the optimal source code lengths to minimize the MSE under this monotone function threshold scheme, subject to a sampling rate constraint.

ArXiv.org
Openalex Percentile: Top 50%
Advanced Data Compression Techniques
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Source Coding for a Wiener Process · ArXiv.org (2025) | TGRS Research Map | TGRS