Strong Converse Exponent for Remote Lossy Source Coding
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866910917130715136 |
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| author | Wu, Han Joudeh, Hamdi |
| author_facet | Wu, Han Joudeh, Hamdi |
| contents | Past works on remote lossy source coding studied the rate under average distortion and the error exponent of excess distortion probability. In this work, we look into how fast the excess distortion probability converges to 1 at small rates, also known as exponential strong converse. We characterize its exponent by establishing matched upper and lower bounds. From the exponent, we also recover two previous results on lossy source coding and biometric authentication. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_14620 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Strong Converse Exponent for Remote Lossy Source Coding Wu, Han Joudeh, Hamdi Information Theory Past works on remote lossy source coding studied the rate under average distortion and the error exponent of excess distortion probability. In this work, we look into how fast the excess distortion probability converges to 1 at small rates, also known as exponential strong converse. We characterize its exponent by establishing matched upper and lower bounds. From the exponent, we also recover two previous results on lossy source coding and biometric authentication. |
| title | Strong Converse Exponent for Remote Lossy Source Coding |
| topic | Information Theory |
| url | https://arxiv.org/abs/2501.14620 |