New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin
2022
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 118 Seiten Illustrationen, Diagramme |
| DOI: | 10.14279/depositonce-16416 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV048553346 | ||
| 003 | DE-604 | ||
| 005 | 20230106 | ||
| 007 | t | ||
| 008 | 221109s2022 a||| m||| 00||| eng d | ||
| 035 | |a (OCoLC)1351546951 | ||
| 035 | |a (DE-599)BVBBV048553346 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-83 | ||
| 084 | |a ST 301 |0 (DE-625)143651: |2 rvk | ||
| 100 | 1 | |a Jamshidi Idaji, Mina |e Verfasser |0 (DE-588)1272554465 |4 aut | |
| 245 | 1 | 0 | |a New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources |
| 264 | 1 | |a Berlin |c 2022 | |
| 300 | |a 118 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 502 | |b Dissertation |c Technische Universität Berlin |d 2022 | ||
| 650 | 0 | 7 | |a Nervennetz |0 (DE-588)4041638-0 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Signaltrennung |0 (DE-588)4181278-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Encephalographie |0 (DE-588)4297453-7 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)4113937-9 |a Hochschulschrift |2 gnd-content | |
| 689 | 0 | 0 | |a Encephalographie |0 (DE-588)4297453-7 |D s |
| 689 | 0 | 1 | |a Nervennetz |0 (DE-588)4041638-0 |D s |
| 689 | 0 | 2 | |a Signaltrennung |0 (DE-588)4181278-5 |D s |
| 689 | 0 | |5 DE-604 | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |o 10.14279/depositonce-16416 |
| 856 | 4 | 1 | |u https://doi.org/10.14279/depositonce-16416 |x Resolving-System |z kostenfrei |3 Volltext |
| 912 | |a ebook | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-033929676 | ||
Datensatz im Suchindex
| _version_ | 1804184560993304576 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Jamshidi Idaji, Mina |
| author_GND | (DE-588)1272554465 |
| author_facet | Jamshidi Idaji, Mina |
| author_role | aut |
| author_sort | Jamshidi Idaji, Mina |
| author_variant | i m j im imj |
| building | Verbundindex |
| bvnumber | BV048553346 |
| classification_rvk | ST 301 |
| collection | ebook |
| ctrlnum | (OCoLC)1351546951 (DE-599)BVBBV048553346 |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| doi_str_mv | 10.14279/depositonce-16416 |
| format | Thesis Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01542nam a2200397 c 4500</leader><controlfield tag="001">BV048553346</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20230106 </controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">221109s2022 a||| m||| 00||| eng d</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1351546951</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV048553346</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-83</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 301</subfield><subfield code="0">(DE-625)143651:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Jamshidi Idaji, Mina</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1272554465</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Berlin</subfield><subfield code="c">2022</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">118 Seiten</subfield><subfield code="b">Illustrationen, Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="502" ind1=" " ind2=" "><subfield code="b">Dissertation</subfield><subfield code="c">Technische Universität Berlin</subfield><subfield code="d">2022</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Nervennetz</subfield><subfield code="0">(DE-588)4041638-0</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Signaltrennung</subfield><subfield code="0">(DE-588)4181278-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Encephalographie</subfield><subfield code="0">(DE-588)4297453-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4113937-9</subfield><subfield code="a">Hochschulschrift</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Encephalographie</subfield><subfield code="0">(DE-588)4297453-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Nervennetz</subfield><subfield code="0">(DE-588)4041638-0</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Signaltrennung</subfield><subfield code="0">(DE-588)4181278-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe</subfield><subfield code="o">10.14279/depositonce-16416</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.14279/depositonce-16416</subfield><subfield code="x">Resolving-System</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ebook</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033929676</subfield></datafield></record></collection> |
| genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV048553346 |
| illustrated | Illustrated |
| index_date | 2024-07-03T20:57:58Z |
| indexdate | 2024-07-10T09:41:17Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033929676 |
| oclc_num | 1351546951 |
| open_access_boolean | 1 |
| owner | DE-83 |
| owner_facet | DE-83 |
| physical | 118 Seiten Illustrationen, Diagramme |
| psigel | ebook |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| record_format | marc |
| spelling | Jamshidi Idaji, Mina Verfasser (DE-588)1272554465 aut New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources Berlin 2022 118 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Dissertation Technische Universität Berlin 2022 Nervennetz (DE-588)4041638-0 gnd rswk-swf Signaltrennung (DE-588)4181278-5 gnd rswk-swf Encephalographie (DE-588)4297453-7 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Encephalographie (DE-588)4297453-7 s Nervennetz (DE-588)4041638-0 s Signaltrennung (DE-588)4181278-5 s DE-604 Erscheint auch als Online-Ausgabe 10.14279/depositonce-16416 https://doi.org/10.14279/depositonce-16416 Resolving-System kostenfrei Volltext |
| spellingShingle | Jamshidi Idaji, Mina New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources Nervennetz (DE-588)4041638-0 gnd Signaltrennung (DE-588)4181278-5 gnd Encephalographie (DE-588)4297453-7 gnd |
| subject_GND | (DE-588)4041638-0 (DE-588)4181278-5 (DE-588)4297453-7 (DE-588)4113937-9 |
| title | New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources |
| title_auth | New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources |
| title_exact_search | New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources |
| title_exact_search_txtP | New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources |
| title_full | New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources |
| title_fullStr | New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources |
| title_full_unstemmed | New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources |
| title_short | New machine learning methods for modeling nonlinear interactions in neural data : towards separation and detection of genuine cross-frequency synchronized sources |
| title_sort | new machine learning methods for modeling nonlinear interactions in neural data towards separation and detection of genuine cross frequency synchronized sources |
| topic | Nervennetz (DE-588)4041638-0 gnd Signaltrennung (DE-588)4181278-5 gnd Encephalographie (DE-588)4297453-7 gnd |
| topic_facet | Nervennetz Signaltrennung Encephalographie Hochschulschrift |
| url | https://doi.org/10.14279/depositonce-16416 |
| work_keys_str_mv | AT jamshidiidajimina newmachinelearningmethodsformodelingnonlinearinteractionsinneuraldatatowardsseparationanddetectionofgenuinecrossfrequencysynchronizedsources |