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Drift removal in plant electrical signals via IIR filtering using wavelet energy

Drift removal in plant electrical signals via IIR filtering using wavelet energy
Drift removal in plant electrical signals via IIR filtering using wavelet energy
Plant electrical signals often contains low frequency drifts with or without the application of external stimuli. Quantification of the randomness in plant signals in a stimulus-specific way is hindered because the knowledge of vital frequency information in the actual biological response is not known yet. Here we design an optimum Infinite Impulse Response (IIR) filter which removes the low frequency drifts and preserves the frequency spectrum corresponding to the random component of the unstimulated plant signals by bringing the bias due to unknown artifacts and drifts to a minimum. We use energy criteria of wavelet packet transform (WPT) for optimization based tuning of the IIR filter parameters. Such an optimum filter enforces that the energy distribution of the pre-stimulus parts in different experiments are almost overlapped but under different stimuli the distributions of the energy get changed. The reported research may popularize plant signal processing, as a separate field, besides other conventional bioelectrical signal processing paradigms.
Plant electrical signal processing, IIR filter, Wavelet packet energy, Optimum filter design
0168-1699
15-23
Das, Saptarshi
e06f2eb0-1e3e-453c-ba78-82eed18ceac9
Ajiwibawa, Barry Juans
cc0a5a1d-48bb-4c4e-85a8-8d185b279865
Chatterjee, Shre Kumar
aaa84ab8-3968-42b1-a9e1-d2a2e03c7b0a
Ghosh, Sanmitra
012cd6b2-63ac-4821-afe3-9b208ba6fd82
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Dasmahapatra, Srinandan
eb5fd76f-4335-4ae9-a88a-20b9e2b3f698
Vitaletti, Andrea
c3fd5ffa-d2eb-4199-9e28-83b5a563e324
Masi, Elisa
f63b0e64-1daf-4c10-a8a5-01823b505d51
Mancuso, Stefano
e9925eea-3fd7-418f-8f30-783f395000a1
Das, Saptarshi
e06f2eb0-1e3e-453c-ba78-82eed18ceac9
Ajiwibawa, Barry Juans
cc0a5a1d-48bb-4c4e-85a8-8d185b279865
Chatterjee, Shre Kumar
aaa84ab8-3968-42b1-a9e1-d2a2e03c7b0a
Ghosh, Sanmitra
012cd6b2-63ac-4821-afe3-9b208ba6fd82
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Dasmahapatra, Srinandan
eb5fd76f-4335-4ae9-a88a-20b9e2b3f698
Vitaletti, Andrea
c3fd5ffa-d2eb-4199-9e28-83b5a563e324
Masi, Elisa
f63b0e64-1daf-4c10-a8a5-01823b505d51
Mancuso, Stefano
e9925eea-3fd7-418f-8f30-783f395000a1

Das, Saptarshi, Ajiwibawa, Barry Juans, Chatterjee, Shre Kumar, Ghosh, Sanmitra, Maharatna, Koushik, Dasmahapatra, Srinandan, Vitaletti, Andrea, Masi, Elisa and Mancuso, Stefano (2015) Drift removal in plant electrical signals via IIR filtering using wavelet energy. Computers and Electronics in Agriculture, 118, 15-23. (doi:10.1016/j.compag.2015.08.013).

Record type: Article

Abstract

Plant electrical signals often contains low frequency drifts with or without the application of external stimuli. Quantification of the randomness in plant signals in a stimulus-specific way is hindered because the knowledge of vital frequency information in the actual biological response is not known yet. Here we design an optimum Infinite Impulse Response (IIR) filter which removes the low frequency drifts and preserves the frequency spectrum corresponding to the random component of the unstimulated plant signals by bringing the bias due to unknown artifacts and drifts to a minimum. We use energy criteria of wavelet packet transform (WPT) for optimization based tuning of the IIR filter parameters. Such an optimum filter enforces that the energy distribution of the pre-stimulus parts in different experiments are almost overlapped but under different stimuli the distributions of the energy get changed. The reported research may popularize plant signal processing, as a separate field, besides other conventional bioelectrical signal processing paradigms.

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Accepted/In Press date: 14 August 2015
e-pub ahead of print date: 29 August 2015
Published date: October 2015
Keywords: Plant electrical signal processing, IIR filter, Wavelet packet energy, Optimum filter design
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 381141
URI: https://eprints.soton.ac.uk/id/eprint/381141
ISSN: 0168-1699
PURE UUID: ac09ecf9-1599-46e8-b2e9-f275b6ed1466

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Date deposited: 02 Sep 2015 13:07
Last modified: 21 Oct 2019 19:08

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Contributors

Author: Saptarshi Das
Author: Barry Juans Ajiwibawa
Author: Sanmitra Ghosh
Author: Koushik Maharatna
Author: Srinandan Dasmahapatra
Author: Andrea Vitaletti
Author: Elisa Masi
Author: Stefano Mancuso

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