Comparison of the Wavelet and Gabor Transforms in the Spectral Analysis of Nonstationary Signals View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-12

AUTHORS

S. V. Bozhokin, I. M. Sokolov

ABSTRACT

Two approaches to the analysis of nonstationary random processes (short-time Fourier transform and continuous wavelet transform) are compared. The comparison is based on the study of several model signals with known time–frequency characteristics. The application of the approaches is also analyzed in the study of spectral dynamics of fluorescence of cold atomic clouds excited by pulsed radiation. It is shown that the two approaches make it possible to reveal the main specific features of the signals under study. However, the continuous wavelet transform has several advantages, since the optimal conditions for the analysis using the short-time Fourier transform are reached if additional calculations aimed at determination of the optimal width of the window are performed. More... »

PAGES

1711-1717

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s1063784218120241

DOI

http://dx.doi.org/10.1134/s1063784218120241

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111749823


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0299", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Other Physical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/02", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Saint Petersburg State Polytechnical University", 
          "id": "https://www.grid.ac/institutes/grid.32495.39", 
          "name": [
            "Peter the Great St. Petersburg Polytechnic University, 195251, St. Petersburg, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bozhokin", 
        "givenName": "S. V.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Saint Petersburg State Polytechnical University", 
          "id": "https://www.grid.ac/institutes/grid.32495.39", 
          "name": [
            "Peter the Great St. Petersburg Polytechnic University, 195251, St. Petersburg, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sokolov", 
        "givenName": "I. M.", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1103/physreva.72.051402", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008879576"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.72.051402", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008879576"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jneumeth.2009.04.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014096696"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/09500340.2012.733431", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015837429"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.neucom.2013.05.027", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016949192"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1018784074", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1018784074", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jneumeth.2005.01.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021819416"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.87.053817", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022059952"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.87.053817", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022059952"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1025271380", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-662-43850-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025271380", 
          "https://doi.org/10.1007/978-3-662-43850-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-662-43850-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025271380", 
          "https://doi.org/10.1007/978-3-662-43850-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.87.063839", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028287407"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.87.063839", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028287407"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1785/0120060255", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029629371"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s1063784212070067", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030123819", 
          "https://doi.org/10.1134/s1063784212070067"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0010-4825(03)00093-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031183969"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0010-4825(03)00093-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031183969"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jelekin.2006.09.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034625213"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1015075101937", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036398419", 
          "https://doi.org/10.1023/a:1015075101937"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s1063784214100065", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038307001", 
          "https://doi.org/10.1134/s1063784214100065"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10916-008-9219-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038603089", 
          "https://doi.org/10.1007/s10916-008-9219-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compbiomed.2004.05.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043773231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.113.133602", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053169798"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.113.133602", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053169798"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.79.033418", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060505561"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.79.033418", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060505561"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.116.083601", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060765076"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.116.083601", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060765076"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.117.073002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060766077"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.117.073002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060766077"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.117.073002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060766077"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.117.073003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060766078"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.117.073003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060766078"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.91.223904", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060827578"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.91.223904", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060827578"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tasl.2007.911054", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061516103"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tasl.2008.919072", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061516256"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tbme.2008.918576", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061527490"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tie.2007.911203", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061623140"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/titb.2010.2058123", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061656933"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpwrd.2009.2034832", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061773169"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/opex.13.002120", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065243834"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.15623/ijret.2013.0212108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068009656"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physa.2017.05.091", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085748709"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s1063784217060068", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086145555", 
          "https://doi.org/10.1134/s1063784217060068"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s1063776117080192", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092336211", 
          "https://doi.org/10.1134/s1063776117080192"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9781139644105", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098698510"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s0030400x17120037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101276789", 
          "https://doi.org/10.1134/s0030400x17120037"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s0030400x17120037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101276789", 
          "https://doi.org/10.1134/s0030400x17120037"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1134/s0030400x17120037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101276789", 
          "https://doi.org/10.1134/s0030400x17120037"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "Two approaches to the analysis of nonstationary random processes (short-time Fourier transform and continuous wavelet transform) are compared. The comparison is based on the study of several model signals with known time\u2013frequency characteristics. The application of the approaches is also analyzed in the study of spectral dynamics of fluorescence of cold atomic clouds excited by pulsed radiation. It is shown that the two approaches make it possible to reveal the main specific features of the signals under study. However, the continuous wavelet transform has several advantages, since the optimal conditions for the analysis using the short-time Fourier transform are reached if additional calculations aimed at determination of the optimal width of the window are performed.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1134/s1063784218120241", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136240", 
        "issn": [
          "0038-5662", 
          "0044-4642"
        ], 
        "name": "Technical Physics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "12", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "63"
      }
    ], 
    "name": "Comparison of the Wavelet and Gabor Transforms in the Spectral Analysis of Nonstationary Signals", 
    "pagination": "1711-1717", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "2d48bffd5979a5cebeeba25b3b7677b1d2ca8138849b77e5bf7dc28c42e89900"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1134/s1063784218120241"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111749823"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1134/s1063784218120241", 
      "https://app.dimensions.ai/details/publication/pub.1111749823"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T08:58", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000326_0000000326/records_68448_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1134%2FS1063784218120241"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1134/s1063784218120241'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1134/s1063784218120241'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1134/s1063784218120241'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1134/s1063784218120241'


 

This table displays all metadata directly associated to this object as RDF triples.

183 TRIPLES      21 PREDICATES      64 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1134/s1063784218120241 schema:about anzsrc-for:02
2 anzsrc-for:0299
3 schema:author N4da3324a14a94d7aa088b4696f2c0fa2
4 schema:citation sg:pub.10.1007/978-3-662-43850-3
5 sg:pub.10.1007/s10916-008-9219-8
6 sg:pub.10.1023/a:1015075101937
7 sg:pub.10.1134/s0030400x17120037
8 sg:pub.10.1134/s1063776117080192
9 sg:pub.10.1134/s1063784212070067
10 sg:pub.10.1134/s1063784214100065
11 sg:pub.10.1134/s1063784217060068
12 https://app.dimensions.ai/details/publication/pub.1018784074
13 https://app.dimensions.ai/details/publication/pub.1025271380
14 https://doi.org/10.1016/j.compbiomed.2004.05.001
15 https://doi.org/10.1016/j.jelekin.2006.09.003
16 https://doi.org/10.1016/j.jneumeth.2005.01.012
17 https://doi.org/10.1016/j.jneumeth.2009.04.006
18 https://doi.org/10.1016/j.neucom.2013.05.027
19 https://doi.org/10.1016/j.physa.2017.05.091
20 https://doi.org/10.1016/s0010-4825(03)00093-3
21 https://doi.org/10.1017/cbo9781139644105
22 https://doi.org/10.1080/09500340.2012.733431
23 https://doi.org/10.1103/physreva.72.051402
24 https://doi.org/10.1103/physreva.79.033418
25 https://doi.org/10.1103/physreva.87.053817
26 https://doi.org/10.1103/physreva.87.063839
27 https://doi.org/10.1103/physrevlett.113.133602
28 https://doi.org/10.1103/physrevlett.116.083601
29 https://doi.org/10.1103/physrevlett.117.073002
30 https://doi.org/10.1103/physrevlett.117.073003
31 https://doi.org/10.1103/physrevlett.91.223904
32 https://doi.org/10.1109/tasl.2007.911054
33 https://doi.org/10.1109/tasl.2008.919072
34 https://doi.org/10.1109/tbme.2008.918576
35 https://doi.org/10.1109/tie.2007.911203
36 https://doi.org/10.1109/titb.2010.2058123
37 https://doi.org/10.1109/tpwrd.2009.2034832
38 https://doi.org/10.1364/opex.13.002120
39 https://doi.org/10.15623/ijret.2013.0212108
40 https://doi.org/10.1785/0120060255
41 schema:datePublished 2018-12
42 schema:datePublishedReg 2018-12-01
43 schema:description Two approaches to the analysis of nonstationary random processes (short-time Fourier transform and continuous wavelet transform) are compared. The comparison is based on the study of several model signals with known time–frequency characteristics. The application of the approaches is also analyzed in the study of spectral dynamics of fluorescence of cold atomic clouds excited by pulsed radiation. It is shown that the two approaches make it possible to reveal the main specific features of the signals under study. However, the continuous wavelet transform has several advantages, since the optimal conditions for the analysis using the short-time Fourier transform are reached if additional calculations aimed at determination of the optimal width of the window are performed.
44 schema:genre research_article
45 schema:inLanguage en
46 schema:isAccessibleForFree false
47 schema:isPartOf N49b7af4c466a4406806bcf1b71b20618
48 Nc522e7ffd5e2461fb2681d6dc4b8352d
49 sg:journal.1136240
50 schema:name Comparison of the Wavelet and Gabor Transforms in the Spectral Analysis of Nonstationary Signals
51 schema:pagination 1711-1717
52 schema:productId N1db753290e9549a3bb3025a503137b6b
53 N261eed39f67947c5b254a1f99894e6c2
54 N5bc11975c71248c09d38884e372a1829
55 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111749823
56 https://doi.org/10.1134/s1063784218120241
57 schema:sdDatePublished 2019-04-11T08:58
58 schema:sdLicense https://scigraph.springernature.com/explorer/license/
59 schema:sdPublisher N1dd67d5bf2c948179d97b0ff68cd1c75
60 schema:url https://link.springer.com/10.1134%2FS1063784218120241
61 sgo:license sg:explorer/license/
62 sgo:sdDataset articles
63 rdf:type schema:ScholarlyArticle
64 N1db753290e9549a3bb3025a503137b6b schema:name dimensions_id
65 schema:value pub.1111749823
66 rdf:type schema:PropertyValue
67 N1dd67d5bf2c948179d97b0ff68cd1c75 schema:name Springer Nature - SN SciGraph project
68 rdf:type schema:Organization
69 N2043e1cc8f7f480ab8bebf950c9fe3d1 rdf:first N65c344e1c7bc4e6d9aa2e98160c8317c
70 rdf:rest rdf:nil
71 N24585dfbed874c6294be0ef6a96dedad schema:affiliation https://www.grid.ac/institutes/grid.32495.39
72 schema:familyName Bozhokin
73 schema:givenName S. V.
74 rdf:type schema:Person
75 N261eed39f67947c5b254a1f99894e6c2 schema:name doi
76 schema:value 10.1134/s1063784218120241
77 rdf:type schema:PropertyValue
78 N49b7af4c466a4406806bcf1b71b20618 schema:issueNumber 12
79 rdf:type schema:PublicationIssue
80 N4da3324a14a94d7aa088b4696f2c0fa2 rdf:first N24585dfbed874c6294be0ef6a96dedad
81 rdf:rest N2043e1cc8f7f480ab8bebf950c9fe3d1
82 N5bc11975c71248c09d38884e372a1829 schema:name readcube_id
83 schema:value 2d48bffd5979a5cebeeba25b3b7677b1d2ca8138849b77e5bf7dc28c42e89900
84 rdf:type schema:PropertyValue
85 N65c344e1c7bc4e6d9aa2e98160c8317c schema:affiliation https://www.grid.ac/institutes/grid.32495.39
86 schema:familyName Sokolov
87 schema:givenName I. M.
88 rdf:type schema:Person
89 Nc522e7ffd5e2461fb2681d6dc4b8352d schema:volumeNumber 63
90 rdf:type schema:PublicationVolume
91 anzsrc-for:02 schema:inDefinedTermSet anzsrc-for:
92 schema:name Physical Sciences
93 rdf:type schema:DefinedTerm
94 anzsrc-for:0299 schema:inDefinedTermSet anzsrc-for:
95 schema:name Other Physical Sciences
96 rdf:type schema:DefinedTerm
97 sg:journal.1136240 schema:issn 0038-5662
98 0044-4642
99 schema:name Technical Physics
100 rdf:type schema:Periodical
101 sg:pub.10.1007/978-3-662-43850-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025271380
102 https://doi.org/10.1007/978-3-662-43850-3
103 rdf:type schema:CreativeWork
104 sg:pub.10.1007/s10916-008-9219-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038603089
105 https://doi.org/10.1007/s10916-008-9219-8
106 rdf:type schema:CreativeWork
107 sg:pub.10.1023/a:1015075101937 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036398419
108 https://doi.org/10.1023/a:1015075101937
109 rdf:type schema:CreativeWork
110 sg:pub.10.1134/s0030400x17120037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101276789
111 https://doi.org/10.1134/s0030400x17120037
112 rdf:type schema:CreativeWork
113 sg:pub.10.1134/s1063776117080192 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092336211
114 https://doi.org/10.1134/s1063776117080192
115 rdf:type schema:CreativeWork
116 sg:pub.10.1134/s1063784212070067 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030123819
117 https://doi.org/10.1134/s1063784212070067
118 rdf:type schema:CreativeWork
119 sg:pub.10.1134/s1063784214100065 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038307001
120 https://doi.org/10.1134/s1063784214100065
121 rdf:type schema:CreativeWork
122 sg:pub.10.1134/s1063784217060068 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086145555
123 https://doi.org/10.1134/s1063784217060068
124 rdf:type schema:CreativeWork
125 https://app.dimensions.ai/details/publication/pub.1018784074 schema:CreativeWork
126 https://app.dimensions.ai/details/publication/pub.1025271380 schema:CreativeWork
127 https://doi.org/10.1016/j.compbiomed.2004.05.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043773231
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.jelekin.2006.09.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034625213
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.jneumeth.2005.01.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021819416
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/j.jneumeth.2009.04.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014096696
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1016/j.neucom.2013.05.027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016949192
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/j.physa.2017.05.091 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085748709
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/s0010-4825(03)00093-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031183969
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1017/cbo9781139644105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098698510
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1080/09500340.2012.733431 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015837429
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1103/physreva.72.051402 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008879576
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1103/physreva.79.033418 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060505561
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1103/physreva.87.053817 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022059952
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1103/physreva.87.063839 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028287407
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1103/physrevlett.113.133602 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053169798
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1103/physrevlett.116.083601 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060765076
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1103/physrevlett.117.073002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060766077
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1103/physrevlett.117.073003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060766078
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1103/physrevlett.91.223904 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060827578
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1109/tasl.2007.911054 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061516103
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1109/tasl.2008.919072 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061516256
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1109/tbme.2008.918576 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061527490
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1109/tie.2007.911203 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061623140
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1109/titb.2010.2058123 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061656933
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1109/tpwrd.2009.2034832 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061773169
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1364/opex.13.002120 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065243834
176 rdf:type schema:CreativeWork
177 https://doi.org/10.15623/ijret.2013.0212108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068009656
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1785/0120060255 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029629371
180 rdf:type schema:CreativeWork
181 https://www.grid.ac/institutes/grid.32495.39 schema:alternateName Saint Petersburg State Polytechnical University
182 schema:name Peter the Great St. Petersburg Polytechnic University, 195251, St. Petersburg, Russia
183 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...