The Karhunen–Loève Transform (KLT) is prevalent nowadays in communication and
signal processing. This thesis aims at attaining the KLT in the encoders and achieving
the minimum sum rate in the case of Gaussian multiterminal source coding.
In the general multiterminal source coding case, the data collected at the terminals
will be compressed in a distributed manner, then communicated the fusion center
for reconstruction. The data source is assumed to be a Gaussian random vector in
this thesis. We introduce the rate-distortion function to formulate the optimization
problem. The rate-distortion function focuses on achieving the minimum encoding
sum rate, subject to a given distortion. The main purpose in the thesis is to propose a
distributed KLT for encoders to deal with the sampled data and produce the minimum
sum rate.
To determine the distributed Karhunen–Loève transform, we propose three kinds
of algorithms. The rst iterative algorithm is derived directly from the saddle point
analysis of the optimization problem. Then we come up with another algorithm by
combining the original rate-distortion function with Wyner's common information,
and this algorithm still has to be solved in an iterative way. Moreover, we also propose
algorithms without iterations. This kind of algorithms will generate the unknown
variables from the existing variables and calculate the result directly.All those algorithms can make the lower-bound and upper-bound of the minimum
sum rate converge, for the gap can be reduced to a relatively small range comparing
to the value of the upper-bound and lower-bound. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/24119 |
| Date | January 2018 |
| Creators | Zhao, Xiaoyu |
| Contributors | Chen, Jun, Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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