Fast gaussian random number generation using linear transformations View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1997-06

AUTHORS

T. Herendi, T. Siegl, R. F. Tichy

ABSTRACT

We develop a method for generating pseudorandom sequences with Gaussian distribution. The method is based on completely uniformly distributed sequences and linear transformations, such as the Fourier transform and Walsh transform. We obtain some discrepancy estimates and make a numerical comparison of these two transformations. Furthermore, we show how this method can be used for testing randomness. We remark that similar approaches are due to Gut, Egorov and Il’in [7], Yuen [26] and Rader [21]. More... »

PAGES

163-181

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf02684478

DOI

http://dx.doi.org/10.1007/bf02684478

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1023101854


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/2008/0399", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Other Chemical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/03", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Debrecen", 
          "id": "https://www.grid.ac/institutes/grid.7122.6", 
          "name": [
            "Department of Mathematics, Kossuth Lajos University, Egyetem t\u00e9r 1, 4010, Debrecen, Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Herendi", 
        "givenName": "T.", 
        "id": "sg:person.01044425457.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01044425457.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Graz University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.410413.3", 
          "name": [
            "Institut f\u00fcr Mathematik, Technische Universit\u00e4t Graz, Steyrergasse 30, 8010, Graz, Austria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Siegl", 
        "givenName": "T.", 
        "id": "sg:person.014655076544.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014655076544.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Graz University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.410413.3", 
          "name": [
            "Institut f\u00fcr Mathematik, Technische Universit\u00e4t Graz, Steyrergasse 30, 8010, Graz, Austria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tichy", 
        "givenName": "R. F.", 
        "id": "sg:person.015312676677.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015312676677.43"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/0041-5553(86)90097-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001936921"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01190941", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009768183", 
          "https://doi.org/10.1007/bf01190941"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01190941", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009768183", 
          "https://doi.org/10.1007/bf01190941"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1112/plms/s2-34.1.241", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011274719"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4613-8643-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035447677", 
          "https://doi.org/10.1007/978-1-4613-8643-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4613-8643-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035447677", 
          "https://doi.org/10.1007/978-1-4613-8643-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-81929-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036529734", 
          "https://doi.org/10.1007/978-3-642-81929-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-81929-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036529734", 
          "https://doi.org/10.1007/978-3-642-81929-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01386213", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039240447", 
          "https://doi.org/10.1007/bf01386213"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02239745", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039666333", 
          "https://doi.org/10.1007/bf02239745"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02239745", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039666333", 
          "https://doi.org/10.1007/bf02239745"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aoms/1177706645", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043005266"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-247x(88)90249-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045877707"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bfb0096980", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051748876", 
          "https://doi.org/10.1007/bfb0096980"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tc.1977.1674842", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061531847"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3905/jpm.1995.409541", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071563710"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/1.9781611970081", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098552246"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1997-06", 
    "datePublishedReg": "1997-06-01", 
    "description": "We develop a method for generating pseudorandom sequences with Gaussian distribution. The method is based on completely uniformly distributed sequences and linear transformations, such as the Fourier transform and Walsh transform. We obtain some discrepancy estimates and make a numerical comparison of these two transformations. Furthermore, we show how this method can be used for testing randomness. We remark that similar approaches are due to Gut, Egorov and Il\u2019in [7], Yuen [26] and Rader [21].", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/bf02684478", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1356894", 
        "issn": [
          "1521-9615", 
          "1436-5057"
        ], 
        "name": "Computing", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "59"
      }
    ], 
    "name": "Fast gaussian random number generation using linear transformations", 
    "pagination": "163-181", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "6e0fdae48684de2cc80b31a6df81cbc695f427c07e5d92967536d767b1f1bf54"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/bf02684478"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1023101854"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/bf02684478", 
      "https://app.dimensions.ai/details/publication/pub.1023101854"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:34", 
    "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/v90/0000000370_0000000370/records_46772_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2FBF02684478"
  }
]
 

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.10.1007/bf02684478'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/bf02684478'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf02684478'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf02684478'


 

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

123 TRIPLES      21 PREDICATES      40 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/bf02684478 schema:about anzsrc-for:03
2 anzsrc-for:0399
3 schema:author N894225e11768429dad34177dec08ae18
4 schema:citation sg:pub.10.1007/978-1-4613-8643-8
5 sg:pub.10.1007/978-3-642-81929-2
6 sg:pub.10.1007/bf01190941
7 sg:pub.10.1007/bf01386213
8 sg:pub.10.1007/bf02239745
9 sg:pub.10.1007/bfb0096980
10 https://doi.org/10.1016/0022-247x(88)90249-1
11 https://doi.org/10.1016/0041-5553(86)90097-2
12 https://doi.org/10.1109/tc.1977.1674842
13 https://doi.org/10.1112/plms/s2-34.1.241
14 https://doi.org/10.1137/1.9781611970081
15 https://doi.org/10.1214/aoms/1177706645
16 https://doi.org/10.3905/jpm.1995.409541
17 schema:datePublished 1997-06
18 schema:datePublishedReg 1997-06-01
19 schema:description We develop a method for generating pseudorandom sequences with Gaussian distribution. The method is based on completely uniformly distributed sequences and linear transformations, such as the Fourier transform and Walsh transform. We obtain some discrepancy estimates and make a numerical comparison of these two transformations. Furthermore, we show how this method can be used for testing randomness. We remark that similar approaches are due to Gut, Egorov and Il’in [7], Yuen [26] and Rader [21].
20 schema:genre research_article
21 schema:inLanguage en
22 schema:isAccessibleForFree false
23 schema:isPartOf N698d3654634546ec8e7b6f5ad74374e1
24 Nd990b52990954308b3266aa0637881e0
25 sg:journal.1356894
26 schema:name Fast gaussian random number generation using linear transformations
27 schema:pagination 163-181
28 schema:productId N482c00adda704ee3b895bfffa1a6a4ca
29 N6c58853543a64c0e86225548b2706a95
30 Nf1dc4e192c604b7b85fce1fc65b20f02
31 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023101854
32 https://doi.org/10.1007/bf02684478
33 schema:sdDatePublished 2019-04-11T13:34
34 schema:sdLicense https://scigraph.springernature.com/explorer/license/
35 schema:sdPublisher Nd8d7825bf3fc42df91b837e38be3743c
36 schema:url http://link.springer.com/10.1007%2FBF02684478
37 sgo:license sg:explorer/license/
38 sgo:sdDataset articles
39 rdf:type schema:ScholarlyArticle
40 N482c00adda704ee3b895bfffa1a6a4ca schema:name dimensions_id
41 schema:value pub.1023101854
42 rdf:type schema:PropertyValue
43 N698d3654634546ec8e7b6f5ad74374e1 schema:issueNumber 2
44 rdf:type schema:PublicationIssue
45 N6c58853543a64c0e86225548b2706a95 schema:name readcube_id
46 schema:value 6e0fdae48684de2cc80b31a6df81cbc695f427c07e5d92967536d767b1f1bf54
47 rdf:type schema:PropertyValue
48 N894225e11768429dad34177dec08ae18 rdf:first sg:person.01044425457.46
49 rdf:rest N89f42e82b48d47429c603d569d7757d9
50 N89f42e82b48d47429c603d569d7757d9 rdf:first sg:person.014655076544.62
51 rdf:rest N9893e70884ee450f8bc7b66f57c75da3
52 N9893e70884ee450f8bc7b66f57c75da3 rdf:first sg:person.015312676677.43
53 rdf:rest rdf:nil
54 Nd8d7825bf3fc42df91b837e38be3743c schema:name Springer Nature - SN SciGraph project
55 rdf:type schema:Organization
56 Nd990b52990954308b3266aa0637881e0 schema:volumeNumber 59
57 rdf:type schema:PublicationVolume
58 Nf1dc4e192c604b7b85fce1fc65b20f02 schema:name doi
59 schema:value 10.1007/bf02684478
60 rdf:type schema:PropertyValue
61 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
62 schema:name Chemical Sciences
63 rdf:type schema:DefinedTerm
64 anzsrc-for:0399 schema:inDefinedTermSet anzsrc-for:
65 schema:name Other Chemical Sciences
66 rdf:type schema:DefinedTerm
67 sg:journal.1356894 schema:issn 1436-5057
68 1521-9615
69 schema:name Computing
70 rdf:type schema:Periodical
71 sg:person.01044425457.46 schema:affiliation https://www.grid.ac/institutes/grid.7122.6
72 schema:familyName Herendi
73 schema:givenName T.
74 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01044425457.46
75 rdf:type schema:Person
76 sg:person.014655076544.62 schema:affiliation https://www.grid.ac/institutes/grid.410413.3
77 schema:familyName Siegl
78 schema:givenName T.
79 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014655076544.62
80 rdf:type schema:Person
81 sg:person.015312676677.43 schema:affiliation https://www.grid.ac/institutes/grid.410413.3
82 schema:familyName Tichy
83 schema:givenName R. F.
84 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015312676677.43
85 rdf:type schema:Person
86 sg:pub.10.1007/978-1-4613-8643-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035447677
87 https://doi.org/10.1007/978-1-4613-8643-8
88 rdf:type schema:CreativeWork
89 sg:pub.10.1007/978-3-642-81929-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036529734
90 https://doi.org/10.1007/978-3-642-81929-2
91 rdf:type schema:CreativeWork
92 sg:pub.10.1007/bf01190941 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009768183
93 https://doi.org/10.1007/bf01190941
94 rdf:type schema:CreativeWork
95 sg:pub.10.1007/bf01386213 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039240447
96 https://doi.org/10.1007/bf01386213
97 rdf:type schema:CreativeWork
98 sg:pub.10.1007/bf02239745 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039666333
99 https://doi.org/10.1007/bf02239745
100 rdf:type schema:CreativeWork
101 sg:pub.10.1007/bfb0096980 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051748876
102 https://doi.org/10.1007/bfb0096980
103 rdf:type schema:CreativeWork
104 https://doi.org/10.1016/0022-247x(88)90249-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045877707
105 rdf:type schema:CreativeWork
106 https://doi.org/10.1016/0041-5553(86)90097-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001936921
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1109/tc.1977.1674842 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061531847
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1112/plms/s2-34.1.241 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011274719
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1137/1.9781611970081 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098552246
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1214/aoms/1177706645 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043005266
115 rdf:type schema:CreativeWork
116 https://doi.org/10.3905/jpm.1995.409541 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071563710
117 rdf:type schema:CreativeWork
118 https://www.grid.ac/institutes/grid.410413.3 schema:alternateName Graz University of Technology
119 schema:name Institut für Mathematik, Technische Universität Graz, Steyrergasse 30, 8010, Graz, Austria
120 rdf:type schema:Organization
121 https://www.grid.ac/institutes/grid.7122.6 schema:alternateName University of Debrecen
122 schema:name Department of Mathematics, Kossuth Lajos University, Egyetem tér 1, 4010, Debrecen, Hungary
123 rdf:type schema:Organization
 




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


...