A sampled-data approach to optimal non-causal downsampling

Hanumant Shekhawat; Gjerrit Meinsma

doi:10.1007/s00498-015-0141-6

A sampled-data approach to optimal non-causal downsampling

Hanumant Shekhawat
, Gjerrit Meinsma

Research output: Contribution to journal › Article › Academic › peer-review

2 Citations (Scopus)

70 Downloads (Pure)

Abstract

Downsampling is the process of reducing the sampling rate of a discrete signal. This paper describes how sampled data system theory can be used to design an L2 or L∞ optimal downsampler which reduces the sampling rate by a positive integer factor from a given fast sampler. This paper also describes the effect of noise on the optimal downsampling.

Original language	English
Pages (from-to)	277-315
Number of pages	39
Journal	Mathematics of control, signals and systems
Volume	27
Issue number	3
DOIs	https://doi.org/10.1007/s00498-015-0141-6
Publication status	Published - Sept 2015

Keywords

2024 OA procedure
Linearity
Sampling
Shannon’s sampling theorem
Time-shift invariance
Causality
System norms

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10.1007/s00498-015-0141-6

ArticleFinal published version, 998 KBLicence: Taverne

Cite this

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abstract = "Downsampling is the process of reducing the sampling rate of a discrete signal. This paper describes how sampled data system theory can be used to design an L2 or L∞ optimal downsampler which reduces the sampling rate by a positive integer factor from a given fast sampler. This paper also describes the effect of noise on the optimal downsampling.",

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KW - 2024 OA procedure

KW - Linearity

KW - Sampling

KW - Shannon’s sampling theorem

KW - Time-shift invariance

KW - Causality

KW - System norms

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A sampled-data approach to optimal non-causal downsampling

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Keywords

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