{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:54:30Z","timestamp":1776088470412,"version":"3.50.1"},"reference-count":0,"publisher":"Slovenian Association Informatika","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJCAI"],"abstract":"<jats:p>This paper presents a comparative study of two learning pipelines that learn intelligent spectrum sensing from Quadrature Phase-Shift Keying (QPSK) In-phase\/Quadrature (I\/Q) data generated in GNU Radio. Both pipelines used two-band Short-Time Fourier Transform (STFT) features with pseudo-labeling based on energy detection. The first pipeline uses a classification approach using Random Forest (RF)on raw STFT features, whereas the second pipeline follows neuro-fuzzy processing of STFT features before classification within a Support Vector Machine (SVM) framework, hence the naming: Fuzzy STFT-SVM (FuST-SVM). Experiments conducted under low (-10dB), medium (5dB), and high (10dB) Signal-to-Noise Ratio (SNR) conditions reveal the dominance of FuST-SVM, with accuracy scores anywhere between 90.65 and 92.46%. The work demonstrates a highly effective and robust solution for the reliable sensing of the spectrum under harsh and heterogeneous noise environments.<\/jats:p>","DOI":"10.31449\/inf.v50i1.12154","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:05:48Z","timestamp":1776085548000},"source":"Crossref","is-referenced-by-count":0,"title":["A Fuzzy Short-Time Fourier Transform and Support Vector Machine Framework for Reliable Spectrum Sensing in Noisy Wireless Channels"],"prefix":"10.31449","volume":"50","author":[{"given":"Deepa N","family":"Reddy","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"16141","published-online":{"date-parts":[[2026,4,13]]},"container-title":["Informatica"],"original-title":[],"link":[{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/download\/12154\/6605","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/download\/12154\/6605","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:05:48Z","timestamp":1776085548000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.informatica.si\/index.php\/informatica\/article\/view\/12154"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,13]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,4,13]]}},"URL":"https:\/\/doi.org\/10.31449\/inf.v50i1.12154","relation":{},"ISSN":["1854-3871","0350-5596"],"issn-type":[{"value":"1854-3871","type":"electronic"},{"value":"0350-5596","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4,13]]}}}