maximum likelihood detection algorithm
Reduced Complexity Maximum Likelihood Detection in Downlink SDMA Systems
... reduced-complexity maximum-likelihood detection algorithm advocated is summarized in Section IV, along with the portrayal of our soft-bit information generation technique used for invoking ...
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Partial interference cancellation with maximum likelihood sequence detection in FBMC spatial multiplexing system
... (for both FBMC/OQAM and FBMC/QAM) will be affected. Indeed, channel estimation error will lead addi- tional noise to the detected signals. However, according to the considered system model given by Eqs. (8) or (10), the ...
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A novel and maximum likelihood segmentation algorithm for touching and overlapping human chromosome images
... as Maximum-Likelihood segmentation ...segmentation algorithm, after obtaining threshold from binary, the watershed transform was ...edge detection and corresponding segmentation. The Novel ...
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Reduced Complexity Maximum Likelihood Detection in Multiple Antenna Aided Multicarrier Systems
... Search Algorithm (OHRSA)-aided space-time processing method, which may be regarded as an advanced extension of the Com- plex Sphere Decoder (CSD) method, portrayed in ...The algorithm proposed extends the ...
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Achieving low complexity maximum likelihood detection for the 3D MIMO code
... The proposed column switch method is presented in Algorithm 4. The basic idea is to use the tree search to determine the more difficult half part and use the parallel detections to find the easier half part. The ...
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Blind Joint Maximum Likelihood Channel Estimation and Data Detection for SIMO Systems
... joint maximum likelihood (ML) channel estimation and data detection of single- input multiple-output (SIMO) ...optimisation algorithm called the repeated weighted boosting search is employed ...
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Maximum likelihood detection for coded combinerless LINC OFDM systems
... The maximum likelihood (ML) receiver can effectively solve the problem; however, its computational complexity is prohibitedly ...Viterbi algorithm (LVA) decoder, to solve the ...
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Novel maximum likelihood approach for passive detection and localisation of multiple emitters
... estimation algorithm that utilises all measurements generated within a time window by an array of sensors, in order to detect and localise an unknown number of target events ...
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Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
... joint maximum likelihood (ML) channel estimation and data detection for multiple-input multiple-output (MIMO) ...search algorithm called the repeated weighted boosting search is employed at ...
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Readings in Targeted Maximum Likelihood Estimation
... the detection of binding sites in a publicly available dataset of the yeast Saccharomyces ...D/S/A algorithm can be used in a variety of settings including prediction of univariate outcomes (setting used in ...
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Robust and adaptive receiver design for wireless communication systems
... LDPC Low-Density Parity Check Code LSM Likelihood Separation vIetric MA M-algorithm MAP Maximum a posteriori probability MF Matched Filter MLSD \llaximum Likelihood Sequence Detection MM[r] ...
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Maximum Likelihood Detection for Detect and Forward Relay Channels
... In this paper, we aim at providing the destination with a more accurate CSI in its decision criterion. While the idea itself of having perfect CSI is not new [9,11,13], the CSI in the previous works is calculated based ...
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DETECTING EDGES FOR IMAGE REPRESENTATION & DESCRIPTION
... edge detection from images which are one of the most important concerns in digital image and video ...efficient detection of edges in order to make it suitable for representation in number of advancing ...
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Some aspects of estimation for vector time series models
... and algorithm, however, require that the degree of det W(z) equal nv and that the zeros are distinct and in the context of echelon canonical form these conditions cannot be ...
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Non orthogonal multiple access with joint maximum likelihood detection in heterogeneous network
... The throughput performance of the heterogeneous NOMA network with joint ML detection is obtained through system-level simulation. The simulation con- ditions are presented in Table 1. The throughput is calculated ...
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Fuzzy Weighted Gaussian Mixture Model for Feature Reduction
... Weighted Likelihood framework. It is one of the promising techniques to identify the features which are relevant. In review of literature, the common weight finding mechanism is not available for selecting the ...
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Moving Target Estimation in Non-Homogeneous Clutter for MIMO Radar
... and detection for non-stationary target using MIMO radar in non-homogeneous ...a maximum likelihood estimator (MLE) for velocity estimation and general likelihood ratio test (GLRT) for ...
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Globally optimal parameter estimates for nonlinear diffusions
... The absolute continuity of the measures Q ,x,y θ and W ,x,y is well known and the form of the Radon–Nikodym derivative in Theorem 3 follows from Lemma 1 in Beskos et al. (2006) and expressions (A.1) and (A.2) in Appendix ...
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Efficient maximum likelihood pedigree reconstruction
... the likelihood of the profile according to the true pedigree, and the maximum likelihood were ...the maximum likelihood pedigree for each pedigree ...
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Smoothing Algorithms by Constrained Maximum Likelihood
... constrained maximum likelihood, with a fair risk scale determined by constrained maximum likelihood, leading to more robust credit loss ...
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