A Barzilai-Borwein gradient projection method for sparse signal and blurred image restoration
• We compared the proposed algorithm MSP with three similar existing algorithms, namely; SGCS [29], PCG [22] and CGD [30]. • Numerical experiments show that MSP outperforms PCG and CGD in signal recovery problems and it restored image with high quality than SGCS and CGD methods. • The proposed algor...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Abubakar, Auwal Bala [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Umfang: |
20 |
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| Übergeordnetes Werk: |
Enthalten in: Modeling and simulation of electrophoretic deposition coatings - Verma, Kevin ELSEVIER, 2020, engineering and applied mathematics, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:357 ; year:2020 ; number:11 ; pages:7266-7285 ; extent:20 |
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10.1016/j.jfranklin.2020.04.022 |
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| 520 | |a • We compared the proposed algorithm MSP with three similar existing algorithms, namely; SGCS [29], PCG [22] and CGD [30]. • Numerical experiments show that MSP outperforms PCG and CGD in signal recovery problems and it restored image with high quality than SGCS and CGD methods. • The proposed algorithm is an extension of the method for solving signal and image restoration problems. • Some nice properties of the algorithm are that it is derivative-free as well as matrix-free. | ||
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10.1016/j.jfranklin.2020.04.022 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001071.pica (DE-627)ELV050830120 (ELSEVIER)S0016-0032(20)30252-0 DE-627 ger DE-627 rakwb eng 004 VZ Abubakar, Auwal Bala verfasserin aut A Barzilai-Borwein gradient projection method for sparse signal and blurred image restoration 2020 20 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • We compared the proposed algorithm MSP with three similar existing algorithms, namely; SGCS [29], PCG [22] and CGD [30]. • Numerical experiments show that MSP outperforms PCG and CGD in signal recovery problems and it restored image with high quality than SGCS and CGD methods. • The proposed algorithm is an extension of the method for solving signal and image restoration problems. • Some nice properties of the algorithm are that it is derivative-free as well as matrix-free. Kumam, Poom oth Mohammad, Hassan oth Awwal, Aliyu Muhammed oth Enthalten in Elsevier Science Verma, Kevin ELSEVIER Modeling and simulation of electrophoretic deposition coatings 2020 engineering and applied mathematics Amsterdam [u.a.] (DE-627)ELV003960617 volume:357 year:2020 number:11 pages:7266-7285 extent:20 https://doi.org/10.1016/j.jfranklin.2020.04.022 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 357 2020 11 7266-7285 20 |
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A Barzilai-Borwein gradient projection method for sparse signal and blurred image restoration |
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• We compared the proposed algorithm MSP with three similar existing algorithms, namely; SGCS [29], PCG [22] and CGD [30]. • Numerical experiments show that MSP outperforms PCG and CGD in signal recovery problems and it restored image with high quality than SGCS and CGD methods. • The proposed algorithm is an extension of the method for solving signal and image restoration problems. • Some nice properties of the algorithm are that it is derivative-free as well as matrix-free. |
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• We compared the proposed algorithm MSP with three similar existing algorithms, namely; SGCS [29], PCG [22] and CGD [30]. • Numerical experiments show that MSP outperforms PCG and CGD in signal recovery problems and it restored image with high quality than SGCS and CGD methods. • The proposed algorithm is an extension of the method for solving signal and image restoration problems. • Some nice properties of the algorithm are that it is derivative-free as well as matrix-free. |
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• We compared the proposed algorithm MSP with three similar existing algorithms, namely; SGCS [29], PCG [22] and CGD [30]. • Numerical experiments show that MSP outperforms PCG and CGD in signal recovery problems and it restored image with high quality than SGCS and CGD methods. • The proposed algorithm is an extension of the method for solving signal and image restoration problems. • Some nice properties of the algorithm are that it is derivative-free as well as matrix-free. |
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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">ELV050830120</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230624170246.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">200722s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.jfranklin.2020.04.022</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001071.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV050830120</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0016-0032(20)30252-0</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">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Abubakar, Auwal Bala</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A Barzilai-Borwein gradient projection method for sparse signal and blurred image restoration</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">20</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">• We compared the proposed algorithm MSP with three similar existing algorithms, namely; SGCS [29], PCG [22] and CGD [30]. • Numerical experiments show that MSP outperforms PCG and CGD in signal recovery problems and it restored image with high quality than SGCS and CGD methods. • The proposed algorithm is an extension of the method for solving signal and image restoration problems. • Some nice properties of the algorithm are that it is derivative-free as well as matrix-free.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kumam, Poom</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mohammad, Hassan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Awwal, Aliyu Muhammed</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Verma, Kevin ELSEVIER</subfield><subfield code="t">Modeling and simulation of electrophoretic deposition coatings</subfield><subfield code="d">2020</subfield><subfield code="d">engineering and applied mathematics</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV003960617</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:357</subfield><subfield code="g">year:2020</subfield><subfield code="g">number:11</subfield><subfield code="g">pages:7266-7285</subfield><subfield code="g">extent:20</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.jfranklin.2020.04.022</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">357</subfield><subfield code="j">2020</subfield><subfield code="e">11</subfield><subfield code="h">7266-7285</subfield><subfield code="g">20</subfield></datafield></record></collection>
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