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ज़ीरो-फोर्सिंग और न्यूनतम माध्य-वर्ग त्रुटि समकरण×शैनन चैनल क्षमता प्रमेय×
क्षेत्रदूरसंचारदूरसंचार
परिवारProcess / pipelineProcess / pipeline
उद्भव वर्ष19741948
प्रवर्तकSaleh Mansour and Paul ZervosClaude Shannon
प्रकारlinear equalization algorithmfundamental theoretical bound
मौलिक स्रोतProakis, J. G. (2001). Digital Communications (4th ed.). McGraw-Hill. link ↗Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423. DOI ↗
उपनामchannel equalization, interference cancellationchannel capacity, information theory bound
संबंधित55
सारांशZero-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.
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ScholarGateविधियों की तुलना करें: ZF/MMSE Equalization · Shannon Capacity. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare