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This paper proposes a new method of extracting and tracking
a nonrigid object moving while allowing camera movement. For object
extraction we first detect an object using watershed segmentation
technique and then extract its contour points by a
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几种 MIMO 最大似然检测算法性能与复杂度比较及改进，介绍了半定松弛、分枝定界和堆栈三种低复杂度最大似然检测算法，并对其性能和复杂度进行了仿真分析，提出了改进的分枝定界和堆栈算法，仿真结果证明分枝定界和堆栈算法性能要优于半定松弛算法，分枝定界算法的复杂度低于堆栈算法且半定松弛算法以多项式复杂度取得了逼近最大似然的性能，同时改进算法加快了算法收敛速度，降低了计算复杂度和对存储空间的要求。
-Several maximum likelihood MIMO detection algorithm
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为了减少无线信道中存在的多径和频偏对中国移动多媒体广播(CMMB)系统传输信号同步的影响，本文结合CMMB标准协议规定的具体帧结构，分析了符号同步对系统的影响，讨论了传统最大似然(ML)算法的优缺点，并基于文献中的无数据辅助算法，提出了一种适合该系统并且复杂度较低的粗符号定时同步算法。仿真结果表明，在AWGN及多径信道环境下，新算法可以有效克服传统算法相关峰不明显的缺陷，其估计性能更好-In order to reduce the influence for synchronization of
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Using SAS/IML :
This code uses the EM algorithm to estimate the maximum likelihood (ML) covariance matrix and mean vector in the presence of missing data. This implementation of the EM algorithm or any similar ML approach assumes that the data are
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8x8 mimo design with near maximum likelihood
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在多输入多输出系统中的鲁棒球形译码的实现-We present a maximum-likelihood decoding algorithm for an
arbitrary lattice code when used over an independent fading channel with
perfect channel state information at the receiver. The decoder is based on
a bounded distanc
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We present a method to learn and recognize object class
models from unlabeled and unsegmented cluttered scenes
in a scale invariant manner. Objects are modeled as flexible
constellations of parts. A probabilistic representation is
used for al
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一种多站测向多目标被动跟踪方法的研究,通过采用最小距离法、最大似然法等方法剔除掉虚假定位点-A multi-station finding the multi-target passive tracking method through the use of the minimum distance method, maximum likelihood method and other methods to weed out the false positioning point
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Adaptive Blind Equalization Using Bottleneck Networks Implemented by Evolvable Hardware.Using a genetic
algorithm, the network on the hardware is trained to
minimize an energy function based on the maximum likelihood
estimation. Simulation resu
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this method is called the maximum likelihood estimation method .which is used to find out the parameters of johnson distribution .
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应用matlab处理统计学问题，含蒙特卡洛算法以及最大似然估计-Statistical analysis and simulation using MATLAB,Monte Carlo simulation and Newton-Raphson method to obtain maximum likelihood estimators are covered.
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We have investigated the performance of the sphere decoding algorithm.
As it has shown in the computer simulations, the decoder based on the
sphere decoding algorithm has almost the same performance of a maximum
likelihood decoder with much low
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介绍了常用的最优估计方法，包括最小二乘发，极大似然估计法，递推法等-The optimal estimation is introduced several kinds of commonly used methods, including least squares, maximum likelihood estimation, recurrence, etc
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This documents explains in details with examples of the use Expectation Maximisation algorithm for maximum likelihood estimation in Gaussian mixtures.
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Maximum Likelihood of Gaussian Distribution for log returns
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An useful note on Maximum Likelihood Estimator(Statistical Signal Processing)
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matlab code for maximum likelihood estimation of noise power
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matlab code for maximum likelihood estimation of signal power
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matlab code for maximum likelihood estimation of signal power and noise power
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efficient matlab code for maximum likelihood estimation of signal power and noise power
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