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- W3208708353 abstract "Choosing the stochastic process with the entropy is attributable to increase the least amount of information to the problem under consideration. As a result, the entropy rate for stochastic processes must be determined. In the current correspondence, we will describe the rate of ‘useful’ conditional Renyi information measure, as well as, show that rate for ‘useful’ Renyi Information, the chain rule holds. Therefore, for the rate of ‘useful’ conditional Renyi information and also for an ergodic Markov chain, we will present a relationship and use it to extract the rate of ‘useful’ Renyi information. At last, we will show that Shannon's information rate is the rate for ‘useful’ Renyi information." @default.
- W3208708353 created "2021-11-08" @default.
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- W3208708353 date "2021-01-01" @default.
- W3208708353 modified "2023-10-02" @default.
- W3208708353 title "Lower and Upper Bounds for ‘Useful’ Renyi Information Rate" @default.
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- W3208708353 doi "https://doi.org/10.1007/978-3-030-88244-0_26" @default.
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