Second Order Analysis for Joint Source-Channel Coding with Markovian Source
Fuente:
arXiv
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2017
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909307596963840 |
|---|---|
| author | Yaguchi, Ryo Hayashi, Masahito |
| author_facet | Yaguchi, Ryo Hayashi, Masahito |
| contents | We derive the second order rates of joint source-channel coding, whose source obeys an irreducible and ergodic Markov process when the channel is a discrete memoryless, while a previous study solved it only in a special case. We also compare the joint source-channel scheme with the separation scheme in the second order regime while a previous study made a notable comparison only with numerical calculation. To make these two notable progress, we introduce two kinds of new distribution families, switched Gaussian convolution distribution and *-product distribution, which are defined by modifying the Gaussian distribution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1701_03290 |
| institution | arXiv |
| publishDate | 2017 |
| record_format | arxiv |
| spellingShingle | Second Order Analysis for Joint Source-Channel Coding with Markovian Source Yaguchi, Ryo Hayashi, Masahito Information Theory We derive the second order rates of joint source-channel coding, whose source obeys an irreducible and ergodic Markov process when the channel is a discrete memoryless, while a previous study solved it only in a special case. We also compare the joint source-channel scheme with the separation scheme in the second order regime while a previous study made a notable comparison only with numerical calculation. To make these two notable progress, we introduce two kinds of new distribution families, switched Gaussian convolution distribution and *-product distribution, which are defined by modifying the Gaussian distribution. |
| title | Second Order Analysis for Joint Source-Channel Coding with Markovian Source |
| topic | Information Theory |
| url | https://arxiv.org/abs/1701.03290 |