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Iterative Linear Minimum-Mean-Square-Error Detection
"... Performance analysis of multi-ary systems with iterative linear minimum-mean-square-error detection ..."
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Performance analysis of multi-ary systems with iterative linear minimum-mean-square-error detection
Notes on Linear Minimum Mean Square Error Estimators
, 2011
"... Some connections between linear minimum mean square error estimators, maximum output SNR filters and the least square solutions are presented. The notes have been prepared to be distributed with EE 503 (METU, Electrical Engin.) lecture notes. 1 Linear Minimum Mean Square Error Estimators The followi ..."
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Some connections between linear minimum mean square error estimators, maximum output SNR filters and the least square solutions are presented. The notes have been prepared to be distributed with EE 503 (METU, Electrical Engin.) lecture notes. 1 Linear Minimum Mean Square Error Estimators
Impact of signaling schemes on iterative linear minimum-mean-square-error detection
- Nov.30 - Dec.4
, 2008
"... Abstract—In this paper, we study the iterative detection problem for a coded system with multi-ary modulation. We show that, with iterative linear minimum-mean-square-error (LMMSE) detection, superposition coded modulation (SCM) can provide performance superior to that with other traditional sig-nal ..."
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Cited by 1 (0 self)
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Abstract—In this paper, we study the iterative detection problem for a coded system with multi-ary modulation. We show that, with iterative linear minimum-mean-square-error (LMMSE) detection, superposition coded modulation (SCM) can provide performance superior to that with other traditional sig
Color demosaicking via directional linear minimum mean square-error estimation
- IEEE Transactions on Image Processing
, 2005
"... Abstract-- Digital color cameras sample scenes using a color filter array of mosaic pattern (e.g. the Bayer pattern). The demosaicking of the color samples is critical to the quality of digital photography. This paper presents a new color demosaicking technique of optimal directional filtering of th ..."
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Cited by 48 (8 self)
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of the green-red and green-blue difference signals. Under the assumption that the primary difference signals (PDS) between the green and red/blue channels are low-pass, the missing green samples are adaptively estimated in both horizontal and vertical directions by the linear minimum mean square-error
Performance Analysis of a Blind Adaptive Linear Minimum Mean Squared Error
"... This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: ..."
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This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available:
PDP ESTIMATION USING LINEAR MINIMUM MEAN SQUARE ERROR IN MIMO-OFDM SYSTEMS
"... Over the recent years, the combination of Multiple Input Multiple Output (MIMO) with Orthogonal Frequency Division Multiplexing (OFDM) has gained significant interest and is considered as one of the most promising techniques for present and future wireless communication systems such as Wi-Max (IEEE ..."
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802.16) or 3rd Generation Partnership Project Long Term Evolution (3GPP LTE). In Linear Minimum Mean Square Error (LMMSE) channel estimation for multicarrier system, it is necessary to know channel correlation function. Hence the estimation of noise variance using null carrier and Power Delay Profile
Performance analysis of multiary systems with iterative linear minimum-mean-square-error detection, in: Proc. 5th Int. Symp. Turbo Codes & Related Topics
- Computer Science, The University of Newcastle
, 2008
"... Abstract—This paper is concerned with coded multi-ary sys-tems over linear channels. Based on a semi-analytical evolution technique, the impact of signaling schemes on the performance of low-cost iterative linear minimum-mean-square-error (LMMSE) detection is studied. It is shown that superposition ..."
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Cited by 1 (0 self)
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Abstract—This paper is concerned with coded multi-ary sys-tems over linear channels. Based on a semi-analytical evolution technique, the impact of signaling schemes on the performance of low-cost iterative linear minimum-mean-square-error (LMMSE) detection is studied. It is shown that superposition
“Color Demosaicking via Directional Linear Minimum Mean-Square-Error Estimation ” [4]. Exact Observed Image Zhang-Wu Demosaicked Image Demosaicking example. The images are enlarged to show individual pixels more clearly. References
"... Most digital cameras capture samples through a color filter array. At every pixel location, the camera observes one of either the red, green, or blue component. Demosaicking (or demosaicing) is the problem of using this incomplete information to estimate all three color components at every pixel. Zh ..."
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Most digital cameras capture samples through a color filter array. At every pixel location, the camera observes one of either the red, green, or blue component. Demosaicking (or demosaicing) is the problem of using this incomplete information to estimate all three color components at every pixel. Zhang and Wu proposed an effective solution to this problem in
Noncoherent Adaptive Linear MMSE Equalization for 16DAPSK Signals
- IEE Electronics Letters
, 1999
"... In this letter, a novel adaptive noncoherent linear minimum mean-squared error (MMSE) equalizer for 16-level differential amplitude/phase-shift keying (16DAPSK) signals is proposed. ..."
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Cited by 1 (1 self)
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In this letter, a novel adaptive noncoherent linear minimum mean-squared error (MMSE) equalizer for 16-level differential amplitude/phase-shift keying (16DAPSK) signals is proposed.
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