Krahasoni metodat

	Ndasi e Ndarë e Burimeve të Verbra	Filtrimi Wiener
Fusha	Përpunimi i sinjaleve	Përpunimi i sinjaleve
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1994	1949
Krijuesi	Pierre Comon	Norbert Wiener
Lloji	Unsupervised signal decomposition	Linear mean-square optimal filter
Burimi themelues	Comon, P. (1994). Independent Component Analysis, a New Concept? Signal Processing, 36(3), 287–314.	Wiener, N. (1949). Extrapolation, Interpolation, and Smoothing of Stationary Time Series. John Wiley & Sons.
Emërtime të tjera	BSS, Blind Signal Separation, Independent Component Analysis, ICA	Wiener Optimal Filter, Kolmogorov-Wiener Filter, Mean-Square Optimal Filter
Të lidhura	4	4
Përmbledhja	Blind Source Separation (BSS) is a signal processing technique that recovers original signals from their unknown mixture without detailed knowledge of the mixing process. Through the framework of Independent Component Analysis (ICA), BSS recovers statistically independent source signals using only the assumption that sources are independent and non-Gaussian. First formalized by Pierre Comon in 1994, BSS has become essential for applications from audio separation to biomedical signal analysis.	The Wiener filter is an optimal linear filter that minimizes mean-square error between the desired signal and the filter output given knowledge of signal and noise statistics. Developed by Norbert Wiener in 1949, it provides the theoretical foundation for optimal filtering and remains the benchmark against which all other linear filtering methods are compared.