This paper presents a noisy channel model based Uyghur harmonized vowel identification method.
该文提出了一种基于噪声信道模型的维吾尔语弱化元音恢复方法。
The evolutionary algorithm is introduced into the design of COVQ to achieve a significant improvement of VQ performance for a given noisy channel status model.
该算法在给定信道状态模型和存在信道噪声的情况下，可以有效地提高矢量量化器的性能，实现了信道最优矢量量化器的设计。
The algorithm achieves a significant improvement of COVQ performance for a given noisy channel status model over other conventional VQ design methods, as confirmed by experimental results.
采用该算法，在给定信道状态模型和信道噪声情况下，可有效地提高矢量量化器的性能，仿真实验结果表明该算法可获得比传统算法更优的性能增益。
The algorithm achieves a significant improvement of COVQ performance for a given noisy channel status model over other conventional VQ design methods, as confirmed by experimental results.
采用该算法，在给定信道状态模型和信道噪声情况下，可有效地提高矢量量化器的性能，仿真实验结果表明该算法可获得比传统算法更优的性能增益。
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