On the Rate of Information Loss in Memoryless Systems
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Summary
It is shown that for a special class of systems the information loss rate is closely related to the difference of differential entropy rates of the input and output processes.
- Type
- preprint
- Published
- 2013-04-18
- Cited by
- 4
- References
- 22
- Access
- Open access
- OpenAlex
- https://openalex.org/W1792498319
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:15947953
Keywords
Markov process, Bounded function, Mathematics, Random variable, Kullback–Leibler divergence
References
- Information Theory: 1948-1998 - Guest Editorial
- Lumpings of Markov Chains, Entropy Rate Preservation, and Higher-Order Lumpability
- A MARKOVIAN FUNCTION OF A MARKOV CHAIN
- Entropy invariance for autoregressive processes constructed by linear filtering
- Rényi Information Dimension: Fundamental Limits of Almost Lossless Analog Compression
- Entropy of the Mixture of Sources and Entropy Dimension
- On the dimension and entropy of probability distributions
- Loss and Recovery of Information by Coarse Observation of Stochastic Chain
- Probability, random variables and stochastic processes
- Some results on the information loss in dynamical systems
- Information and information stability of random variables and processes
- A useful theorem for nonlinear devices having Gaussian inputs
- Information Measures for Deterministic Input-Output Systems
- Lumpings of Markov chains and entropy rate loss
- FINITE MARKOV CHAINS
- Discrete Time Signal Processing
- Functions of a Markov Process that are Markovian
- Lumpings of Markov chains, entropy rate preservation, and higher-order lumpability
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