Comparer des méthodes

	Égalisation par Zéro Forcé et par Erreur Quadratique Moyenne Minimale	Théorème de la capacité de canal de Shannon
Domaine	Télécommunications	Télécommunications
Famille	Process / pipeline	Process / pipeline
Année d'origine	1974	1948
Auteur d'origine	Saleh Mansour and Paul Zervos	Claude Shannon
Type	linear equalization algorithm	fundamental theoretical bound
Source fondatrice	Proakis, J. G. (2001). Digital Communications (4th ed.). McGraw-Hill.	Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423.
Alias	channel equalization, interference cancellation	channel capacity, information theory bound
Apparentées	5	5
Résumé	Zero-Forcing (ZF) and Minimum Mean-Square Error (MMSE) equalization are fundamental linear receiver algorithms for combating intersymbol interference in dispersive channels. Developed in the context of data transmission theory, these methods form the basis of modern channel equalization in wireless and wired systems. While ZF aggressively cancels interference, MMSE balances interference suppression with noise enhancement, making it the optimal linear solution under Gaussian noise.	Shannon's channel capacity theorem, published in 1948, establishes the maximum rate at which information can be reliably transmitted over a noisy channel. Expressed as C = B log2(1 + S/N) for additive white Gaussian noise (AWGN), it is a fundamental bound in information theory and communications engineering. Shannon proved that reliable communication is possible at any rate below capacity, and impossible above it. This theorem underpins the design of all modern communication systems and motivates coding theory, modulation, and signal processing techniques.