Computer Science – Information Theory
Scientific paper
2006-10-24
Computer Science
Information Theory
37 pages, 9 figures. Cleaned up typos and reformatted paper for increased clarity
Scientific paper
Our understanding of information in systems has been based on the foundation of memoryless processes. Extensions to stable Markov and auto-regressive processes are classical. Berger proved a source coding theorem for the marginally unstable Wiener process, but the infinite-horizon exponentially unstable case has been open since Gray's 1970 paper. There were also no theorems showing what is needed to communicate such processes across noisy channels. In this work, we give a fixed-rate source-coding theorem for the infinite-horizon problem of coding an exponentially unstable Markov process. The encoding naturally results in two distinct bitstreams that have qualitatively different QoS requirements for communicating over a noisy medium. The first stream captures the information that is accumulating within the nonstationary process and requires sufficient anytime reliability from the channel used to communicate the process. The second stream captures the historical information that dissipates within the process and is essentially classical. This historical information can also be identified with a natural stable counterpart to the unstable process. A converse demonstrating the fundamentally layered nature of unstable sources is given by means of information-embedding ideas.
Mitter Sanjoy
Sahai Anant
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