Universal prediction of individual sequences

The problem of predicting the next outcome of an individual binary sequence using finite memory is considered. The finite-state predictability of an infinite sequence is defined as the minimum fraction of prediction errors that can be made by any finite-state (FS) predictor. It is proven that this F...

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Vydané v:IEEE transactions on information theory Ročník 38; číslo 4; s. 1258 - 1270
Hlavní autori: Feder, M., Merhav, N., Gutman, M.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York, NY IEEE 01.07.1992
Institute of Electrical and Electronics Engineers
Predmet:
Applied sciences
Binary sequences
Data compression
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Frequency
Information, signal and communications theory
Signal and communications theory
Signal, noise
Telecommunications and information theory
Binary sequence
Compression
Predictor
Prediction
Algorithm
Complexity
Information theory
ISSN:0018-9448
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Shrnutí:The problem of predicting the next outcome of an individual binary sequence using finite memory is considered. The finite-state predictability of an infinite sequence is defined as the minimum fraction of prediction errors that can be made by any finite-state (FS) predictor. It is proven that this FS predictability can be achieved by universal sequential prediction schemes. An efficient prediction procedure based on the incremental parsing procedure of the Lempel-Ziv data compression algorithm is shown to achieve asymptotically the FS predictability. Some relations between compressibility and predictability are discussed, and the predictability is proposed as an additional measure of the complexity of a sequence.< >
Bibliografia:ObjectType-Article-2
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0018-9448
DOI:10.1109/18.144706