SIGNAL TIZIMLARIDA SHOVQINNI KAMAYTIRISH
Keywords:
signalni qayta ishlash, shovqinni kamaytirish, raqamli filtrlar, veyvlet tahlili, SNR, adaptiv algoritmlar, spektral ayirish.Abstract
Ushbu maqolada signal tizimlarida yuzaga keladigan shovqinlarni kamaytirish va signal-shovqin nisbatini (SNR) yaxshilash usullari tahlil qilingan. Tadqiqot davomida klassik raqamli filtrlar, veyvlet o‘zgartirishlari va zamonaviy adaptiv filtrlash algoritmlarining samaradorligi o‘zaro solishtirilgan. Shuningdek, nutq signallarini tozalashda spektral ayirish usulining afzalliklari va cheklovlari ko‘rib chiqilgan. Olingan natijalar shuni ko‘rsatadiki, gibrid usullarni qo‘llash dinamik shovqinli muhitda signal sifatini sezilarli darajada oshiradi. Maqola radioaloqa, tibbiy diagnostika va audio muhandislik sohasida ishlovchi mutaxassislar uchun mo‘ljallangan.
References
Gulyamov, S. S., & Xoldorov, B. B. (2021). Raqamli signallarga ishlov berish: Nazariya va usullar. Toshkent: Fan va texnologiya nashriyoti.
Mallat, S. (2009). A Wavelet Tour of Signal Processing: The Sparse Way. Academic Press.
Haykin, S. (2014). Adaptive Filter Theory. Pearson Education.
Ismatullaev, P. R., & Yusupov, A. S. (2020). Signal tizimlarida shovqinni o‘lchash va kamaytirish usullari. O‘zbekiston aloqa va axborotlashtirish jurnali, (3), 12-18.
Boll, S. (1979). Suppression of acoustic noise in speech using spectral subtraction. IEEE Transactions on Acoustics, Speech, and Signal Processing, 27(2), 113-120.
Widrow, B., & Stearns, S. D. (1985). Adaptive Signal Processing. Prentice-Hall.
Donoho, D. L. (1995). De-noising by soft-thresholding. IEEE Transactions on Information Theory, 41(3), 613-627.
Oppenheim, A. V., & Schafer, R. W. (2010). Discrete-Time Signal Processing. Pearson Higher Education.