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<record>
  <title>A Framework for the Digital Hilbert Transformer with Cascade Realization</title>
  <journal>Digital Signal Processing and Artificial Intelligence for Automatic Learning</journal>
  <author>Kamelia Nikolova and Georgi Stoyanov</author>
  <volume>2</volume>
  <issue>4</issue>
  <year>2023</year>
  <doi>https://doi.org/10.6025/dspaial/2023/2/4/93-101</doi>
  <url>https://www.dline.info/dspai/fulltext/v2n4/dspaiv2n4_1.pdf</url>
  <abstract>In this work, we proposed a framework for the digital Hilbert transformer that can limit 90-degree deviations. We studied the cascade realization of the divisions of the structure to include phase sensitivity minimization of all-pass sections. The design is tested for efficiency, providing acceptable experimental results.</abstract>
</record>
