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- W3105627797 abstract "Computational mechanics quantifies structure in a stochastic process via its causal states, leading to the process's minimal, optimal predictor---the $epsilon$-machine. We extend computational mechanics to communication channels between two processes, obtaining an analogous optimal model---the $epsilon$-transducer---of the stochastic mapping between them. Here, we lay the foundation of a structural analysis of communication channels, treating joint processes and processes with input. The result is a principled structural analysis of mechanisms that support information flow between processes. It is the first in a series on the structural information theory of memoryful channels, channel composition, and allied conditional information measures." @default.
- W3105627797 created "2020-11-23" @default.
- W3105627797 creator A5018730647 @default.
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- W3105627797 date "2015-08-12" @default.
- W3105627797 modified "2023-10-16" @default.
- W3105627797 title "Computational Mechanics of Input–Output Processes: Structured Transformations and the $$epsilon $$-Transducer" @default.
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- W3105627797 doi "https://doi.org/10.1007/s10955-015-1327-5" @default.
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