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Improving autocorrelation and RFM autocorrelation performance of TD-ERCS sequence

Authors: Bin Chen;

Improving autocorrelation and RFM autocorrelation performance of TD-ERCS sequence

Abstract

Chaotic sequences have been widely used as pseudorandom sequences. But some well known chaotic sequence has poor autocorrelation, or after modulation, autocorrelation performance become poor, and their applications are limited. Such as TD-ERCS sequence, not only has poor autocorrelation performance, but also its RFM signal has poor autocorrelation, too. Based on recently presented APAS theorem, we modified TD-ERCS map to DS-TD-ERCS map, and DS-TD-ERCS sequence has excellent autocorrelation and RFM autocorrelation performance and has simple structure, whereas its other performances are remained invariant or become better, and can be used more widely.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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