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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Deep Learning based categorization of modulation methods for wireless communications |
| Authors Name: | Vargil Vijay E , Venkata Ramireddy P , Jubeda M , Padmaja K , Venkateswarlu N |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_192023
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| Published Paper Id: | IJNRD2304398 |
| Published In: | Volume 8 Issue 4, April-2023 |
| DOI: | http://doi.one/10.1729/Journal.33824 |
| Abstract: | Deep learning, a novel approach which is a subset of machine learning, has demonstrated exceptional performance in the processing of images, voices, and natural language. Researchers haven't yet fully analyzed how DL can be used for wireless transmission, though. Recently, it has become more common to use DL technology for wireless communication uses. This article's suitability of a Deep learning-based strategy for classification of modulation methods is discussed. Applications for modulation method classification (MMC) are both private and military. This article proposes a deep learning-based architecture for modulation method classification which is known as Convolutional Neural Network (CNN). In our suggested architecture, we will use a Gaussian noise layer following the convolution layers, which shows a remedial impact during training and lowers the over fitting issue. We want to show that the suggested architecture for modulation classification methods works better than the current machine learning-based architecture. |
| Keywords: | Deep Learning based categorization of modulation methods for wireless communications |
| Cite Article: | "Deep Learning based categorization of modulation methods for wireless communications", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.d712-d719, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304398.pdf |
| Downloads: | 000118797 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2304398 Registration ID: 192023 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.33824 Page No: d712-d719 Country: -, -, - Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2304398 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2304398 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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