Kichujio kinachobadilika cha LMS
Kichujio cha Least Mean Squares (LMS) ni algorithmu ya usindikaji wa mawimbi inayobadilika ambayo husasisha vipengele vya kichujio ili kupunguza makosa ya mraba kati ya pato la kichujio na mawimbi yanayotakiwa. Imeanzishwa na Bernard Widrow na Marcian Hoff mwaka 1960, algorithmu ya LMS ni mojawapo ya mbinu zinazotumiwa sana za uchujaji unaobadilika kutokana na urahisi wake, gharama ndogo ya hesabu, na uwezo wa kufuatilia mawimbi yanayobadilika kwa wakati.
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Method map
The neighbourhood of related methods — select a node to explore.
Vyanzo
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Least Mean Squares Adaptive Filter. ScholarGate. https://scholargate.app/sw/signal-processing/adaptive-lms-filter
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Ubunifu wa Vichujio vya FIRUchakataji wa Mawimbi↔ compare
- Ubunifu wa Vichujio vya Msukumo Usioisha (IIR)Uchakataji wa Mawimbi↔ compare
- Kichujio cha Kalman cha Kufuatilia MawimbiUchakataji wa Mawimbi↔ compare
- Kichujio cha WienerUchakataji wa Mawimbi↔ compare
Imerejelewa na
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