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<record>
  <title>The Single-to-Noise Ratio in Extreme Learning Machines</title>
  <journal>Journal of Data Processing</journal>
  <author>Nikola Sekulovic, MiloÅ¡ Stojanovic, Aleksandra Panajotovic and MiloÅ¡ Bandur</author>
  <volume>13</volume>
  <issue>2</issue>
  <year>2023</year>
  <doi>https://doi.org/10.6025/jdp/2023/13/2/51-57</doi>
  <url>https://www.dline.info/jdp/fulltext/v13n2/jdpv13n2_3.pdf</url>
  <abstract>This work predicted the wireless channel environment on extreme learning machines. The environment we have selected has single output systems in microcellular and picocellualar characteristics. The performance indicators include the average squared error and time consumption for operations. In the experimentation process, we found that the signal-to-noise ratio values reflected less execution time and higher accuracy. </abstract>
</record>
