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dc.contributor.authorZhao, Wenshan
dc.contributor.authorMa, Lina
dc.contributor.authorZhang, Yuzhen
dc.contributor.authorHe, Yigang
dc.contributor.authorSun, Yichuang
dc.date.accessioned2019-12-13T01:09:45Z
dc.date.available2019-12-13T01:09:45Z
dc.date.issued2019-11-20
dc.identifier.citationZhao , W , Ma , L , Zhang , Y , He , Y & Sun , Y 2019 , ' Design of Gm-C wavelet filter for on-line epileptic EEG detection ' , IEICE Electronics Express . https://doi.org/10.1587/elex.16.20190560
dc.identifier.issn1349-2543
dc.identifier.otherPURE: 17827929
dc.identifier.otherPURE UUID: 98aef54a-5a2d-4b8e-a528-8d3035b336e0
dc.identifier.otherScopus: 85078921467
dc.identifier.urihttp://hdl.handle.net/2299/21990
dc.descriptionCopyright © 2019 The Institute of Electronics, Information and Communication Engineers
dc.description.abstractAnalog filter implementation of continuous wavelet transform is considered as a promising technique for on-line spike detection applied in wearable electroencephalogram system. This Letter proposes a novel method to construct analog wavelet base for analog wavelet filter design, in which the mathematical approximation model in frequency domain is built as an optimization problem and the genetic algorithm is used to find the global optimum resolution. Also, the Gm-C filter structure based on LC ladder simulation is employed to synthesize the obtained analog wavelet base. The Marr wavelet filter is designed as an example using SMIC 1V 0.35μm CMOS technology. Simulation results show that the proposed method can give a stable analog wavelet filter with higher approximation accuracy and excellent circuit performance, which is well suited for the design of low-frequency low-power spike detector.en
dc.language.isoeng
dc.relation.ispartofIEICE Electronics Express
dc.titleDesign of Gm-C wavelet filter for on-line epileptic EEG detectionen
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionCommunications and Intelligent Systems
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Engineering and Technology
dc.description.statusPeer reviewed
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1587/elex.16.20190560
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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