Electronically tunable fractional-order highpass filter for phantom electroencephalographic system model implementation
The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Baxevanaki, Kleoniki [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Editorial Board - 2016, München |
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| Übergeordnetes Werk: |
volume:110 ; year:2019 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.aeue.2019.152850 |
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ELV048258261 |
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| 520 | |a The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. | ||
| 520 | |a The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. | ||
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10.1016/j.aeue.2019.152850 doi GBV00000000000787.pica (DE-627)ELV048258261 (ELSEVIER)S1434-8411(19)31465-7 DE-627 ger DE-627 rakwb eng 610 VZ 370 VZ Baxevanaki, Kleoniki verfasserin aut Electronically tunable fractional-order highpass filter for phantom electroencephalographic system model implementation 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. Electroencephalographic systems Elsevier Fractional-order filters Elsevier Fractional-order circuits Elsevier Fractional-order modeling Elsevier Kapoulea, Stavroula oth Psychalinos, Costas oth Elwakil, Ahmed S. oth Enthalten in Elsevier Editorial Board 2016 München (DE-627)ELV019902425 volume:110 year:2019 pages:0 https://doi.org/10.1016/j.aeue.2019.152850 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 110 2019 0 |
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10.1016/j.aeue.2019.152850 doi GBV00000000000787.pica (DE-627)ELV048258261 (ELSEVIER)S1434-8411(19)31465-7 DE-627 ger DE-627 rakwb eng 610 VZ 370 VZ Baxevanaki, Kleoniki verfasserin aut Electronically tunable fractional-order highpass filter for phantom electroencephalographic system model implementation 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. Electroencephalographic systems Elsevier Fractional-order filters Elsevier Fractional-order circuits Elsevier Fractional-order modeling Elsevier Kapoulea, Stavroula oth Psychalinos, Costas oth Elwakil, Ahmed S. oth Enthalten in Elsevier Editorial Board 2016 München (DE-627)ELV019902425 volume:110 year:2019 pages:0 https://doi.org/10.1016/j.aeue.2019.152850 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 110 2019 0 |
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10.1016/j.aeue.2019.152850 doi GBV00000000000787.pica (DE-627)ELV048258261 (ELSEVIER)S1434-8411(19)31465-7 DE-627 ger DE-627 rakwb eng 610 VZ 370 VZ Baxevanaki, Kleoniki verfasserin aut Electronically tunable fractional-order highpass filter for phantom electroencephalographic system model implementation 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. Electroencephalographic systems Elsevier Fractional-order filters Elsevier Fractional-order circuits Elsevier Fractional-order modeling Elsevier Kapoulea, Stavroula oth Psychalinos, Costas oth Elwakil, Ahmed S. oth Enthalten in Elsevier Editorial Board 2016 München (DE-627)ELV019902425 volume:110 year:2019 pages:0 https://doi.org/10.1016/j.aeue.2019.152850 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 110 2019 0 |
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10.1016/j.aeue.2019.152850 doi GBV00000000000787.pica (DE-627)ELV048258261 (ELSEVIER)S1434-8411(19)31465-7 DE-627 ger DE-627 rakwb eng 610 VZ 370 VZ Baxevanaki, Kleoniki verfasserin aut Electronically tunable fractional-order highpass filter for phantom electroencephalographic system model implementation 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. Electroencephalographic systems Elsevier Fractional-order filters Elsevier Fractional-order circuits Elsevier Fractional-order modeling Elsevier Kapoulea, Stavroula oth Psychalinos, Costas oth Elwakil, Ahmed S. oth Enthalten in Elsevier Editorial Board 2016 München (DE-627)ELV019902425 volume:110 year:2019 pages:0 https://doi.org/10.1016/j.aeue.2019.152850 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 110 2019 0 |
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10.1016/j.aeue.2019.152850 doi GBV00000000000787.pica (DE-627)ELV048258261 (ELSEVIER)S1434-8411(19)31465-7 DE-627 ger DE-627 rakwb eng 610 VZ 370 VZ Baxevanaki, Kleoniki verfasserin aut Electronically tunable fractional-order highpass filter for phantom electroencephalographic system model implementation 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. Electroencephalographic systems Elsevier Fractional-order filters Elsevier Fractional-order circuits Elsevier Fractional-order modeling Elsevier Kapoulea, Stavroula oth Psychalinos, Costas oth Elwakil, Ahmed S. oth Enthalten in Elsevier Editorial Board 2016 München (DE-627)ELV019902425 volume:110 year:2019 pages:0 https://doi.org/10.1016/j.aeue.2019.152850 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 110 2019 0 |
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The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. |
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The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. |
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The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV048258261</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626021519.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">191023s2019 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.aeue.2019.152850</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000787.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV048258261</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1434-8411(19)31465-7</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">370</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Baxevanaki, Kleoniki</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Electronically tunable fractional-order highpass filter for phantom electroencephalographic system model implementation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019transfer abstract</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The fractional-order model of a phantom electroencephalographic system, at various distances between electrodes, is realized using appropriate decomposition of the rational transfer functions which approximate the highpass filters that describe its dynamics. 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The main offered benefits, in comparison to the corresponding straightforward implementations of the rational transfer functions, are the capability of monolithic implementation due the minimization of the maximum value of the required capacitances and, also, the reduced power consumption. The performance of the presented filter topologies is evaluated, at post-layout level, using the Cadence design suite.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Electroencephalographic systems</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Fractional-order filters</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Fractional-order circuits</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Fractional-order modeling</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kapoulea, Stavroula</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Psychalinos, Costas</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Elwakil, Ahmed S.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="t">Editorial Board</subfield><subfield code="d">2016</subfield><subfield code="g">München</subfield><subfield code="w">(DE-627)ELV019902425</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:110</subfield><subfield code="g">year:2019</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.aeue.2019.152850</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">110</subfield><subfield code="j">2019</subfield><subfield code="h">0</subfield></datafield></record></collection>
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