Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
PDF Tools
Image Tools
Text Tools
OCR Tools
Symbol and Emoji Tools
On-screen Keyboard
Latex Math Equation to Image
Smart IPA Phonetic Keyboard
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
133
click to vote
CORR
2004
Springer
102
views
Education
»
more
CORR 2004
»
Mutual Information and Minimum Mean-square Error in Gaussian Channels
15 years 3 months ago
Download
www.princeton.edu
Abstract--This paper deals with arbitrarily distributed finitepower input signals observed through an additive Gaussian noise channel. It shows a new formula that connects the input
Dongning Guo, Shlomo Shamai, Sergio Verdú
Real-time Traffic
CORR 2004
|
Education
|
Finitepower Input Signals
|
Input
|
Mutual Information
|
claim paper
Related Content
»
Optimal Precoding for Digital Subscriber Lines
»
Estimation in Gaussian Noise Properties of the Minimum MeanSquare Error
»
Stochastic transceiver design in multiantenna channels with statistical channel state info...
»
MBER Turbo Multiuser Beamforming Aided QPSK Receiver Design Using EXIT Chart Analysis
»
Linear transceiver design in a multiuser MIMO system with quantized channel state informat...
»
On MultiUser EXIT Chart Analysis Aided TurboDetected MBER Beamformer Designs
»
Minimum Symbol Error Rate Turbo Multiuser Beamforming Aided QAM Receiver
»
Nonlinear Channel Equalization With Gaussian Processes for Regression
»
MIMO LMMSE Transceiver Design with Imperfect CSI at Both Ends
more »
Post Info
More Details (n/a)
Added
17 Dec 2010
Updated
17 Dec 2010
Type
Journal
Year
2004
Where
CORR
Authors
Dongning Guo, Shlomo Shamai, Sergio Verdú
Comments
(0)
Researcher Info
Education Study Group
Computer Vision