In this paper, we propose a model-based, self organizing feature map algorithm for the clustering of variable-length sequences.

本文提出一种基于模型的、适合变长符号序列的自组织聚类算法。

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First it introduces TTCM and MAP algorithm and then compares the difference between binary MAP and Symbol by Symbol MAP.

简要介绍TTCM技术及符号MAP算法，并比较了二进制MAP算法与符号MAP算法的差别。

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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。

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In order to attain a high-resolution image, the algorithm is based on the MAP algorithm, solving the optimization by proposed iteration steps with using the gradient projection method.

该方法基于MAP算法，通过利用梯度投影的方法对重建结果不断进行迭代优化得到最终的理想高分辨率影像。

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In order to attain a high-resolution image, the algorithm is based on the MAP algorithm, solving the optimization by proposed iteration steps with using the gradient projection method.

该方法基于MAP算法，通过利用梯度投影的方法对重建结果不断进行迭代优化得到最终的理想高分辨率影像。

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