@prefix dcat: <http://www.w3.org/ns/dcat#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://data.amerigeoss.org/dataset/3caa8642-f0ab-45f3-8a50-8026b06f6e4b> a dcat:Dataset ;
    dct:description "This research software package contains Python code to execute experiments on deep generative modeling of classical random process models for noise time series. Specifically, it includes Pytorch implementations of two generative adversarial network (GAN) models for time series based on convolutational neural networks (CNNs): WaveGAN, a 1-D CNN model, and STFT-GAN, a 2-D CNN model. In addition, there are methods for generating and evaluating noise time series defined several by classical random process models." ;
    dct:identifier "ark:/88434/mds2-2695" ;
    dct:issued "2022-07-08"^^xsd:date ;
    dct:language "{en}" ;
    dct:modified "2022-07-03T00:00:00"^^xsd:dateTime ;
    dct:publisher <https://data.amerigeoss.org/organization/727dbdd5-3f98-4ac0-9d28-5e344558139b> ;
    dct:title "Software for Evaluating Convolutional Generative Adversarial Networks with Classical Random Process Noise Models" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "Adam Wunderlich" ;
            vcard:hasEmail <mailto:adam.wunderlich@nist.gov> ] ;
    dcat:distribution <https://data.amerigeoss.org/dataset/3caa8642-f0ab-45f3-8a50-8026b06f6e4b/resource/f1da63bb-6524-433a-badd-1a330f3df469> ;
    dcat:keyword "amerigeo",
        "amerigeoss",
        "band-limited-noise",
        "ckan",
        "colored-noise",
        "fractional-brownian-motion",
        "fractional-gaussian-noise",
        "geo",
        "geoss",
        "impulsive-noise",
        "machine-learning",
        "national",
        "north-america",
        "power-law-noise",
        "shot-noise",
        "time-series",
        "united-states" ;
    dcat:theme <%22Mathematics%20and%20Statistics:Modeling%20and%20simulation%20research%22%7D>,
        <%7B%22Mathematics%20and%20Statistics:Image%20and%20signal%20processing%22> .

<https://data.amerigeoss.org/dataset/3caa8642-f0ab-45f3-8a50-8026b06f6e4b/resource/f1da63bb-6524-433a-badd-1a330f3df469> a dcat:Distribution ;
    dct:description "GitHub repository" ;
    dct:format "python source code" ;
    dct:issued "2022-07-29T04:19:29.449475"^^xsd:dateTime ;
    dct:modified "2025-11-21T03:04:57.594236"^^xsd:dateTime ;
    dct:title "GitHub repository" ;
    dcat:accessURL <https://github.com/usnistgov/NoiseGAN> .

<https://data.amerigeoss.org/organization/727dbdd5-3f98-4ac0-9d28-5e344558139b> a foaf:Agent ;
    foaf:name "US Migrating" .