While the MAP algorithm offers better performance than the ML algorithm, the computation is complex and not suitable for hardware implementation.
在相同条件下，最大后验概率译码算法比最大似然译码算法有更低误比特率，但由于计算量和复杂度过大而不适合硬件实现。
These two algorithms relax the constraints of ML algorithm and transform it into a convex problem which can be efficiently solved with a polynomial time.
这两类算法是在ML算法基础上放松约束条件，将问题转化为可在多项式时间内解决的凸优化问题。
The result presents that when LAS-CDMA system using 16QAM modulation under AWGN channel, the error probability of sphere decoding goes to theory error probability of ML algorithm.
介绍了球译码算法的工作原理，给出了算法流程；研究结果表明AWGN信道下LAS-CDMA系统使用16QAM调制时，球译码算法差错率趋近于使用基于ML算法的理论差错概率。
A modified MMSE-ML algorithm is proposed, by finding the second probable constellation symbol position after MMSE-ML search, and then applying the ML search on these two positions.
提出了一种改进的MMSE -ML算法，在一阶MMSE - ML搜索的中间结果中找出次最可能的星座符号位置，进而在这两个位置上做ML搜索。
Results of simulation and analysis show that, in comparison with ML algorithm it is of better synchronization performance, and its performance is considerably raised especially in multipath channels.
仿真结果表明，与ML算法相比，该算法大大提高了系统的同步性能，尤其是在多径信道中的性能得到了很大提高。
Based on the temporal-spatial sequential Maximum Likelihood (ML) algorithm, a new algorithm for estimating the elevation Angle of a target in radar low-angle tracking environment is presented.
在时空级联最大似然算法的基础上，本文结合雷达低角跟踪的特点，提出一种新的目标仰角估计算法。
Based on the temporal-spatial sequential Maximum Likelihood (ML) algorithm, a new algorithm for estimating the elevation Angle of a target in radar low-angle tracking environment is presented.
在时空级联最大似然算法的基础上，本文结合雷达低角跟踪的特点，提出一种新的目标仰角估计算法。
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