This paper introduced a local cosine-basis based dictionary, it segments the time frame and ADAPTS speech signal's changes of the time-frequency structure.

构造局部余弦基字典，其对时间轴的分割适应于语音信号时频结构的变化，而且有较高的时频分辨率。

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In order to solve these problems, we proposed a single feature vector recognition model based on whole time-frequency information structure of digit speech.

为了解决这些问题，我们提出了基于数字语音时频信息整体结构的单特征向量识别模型。

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By exploiting wavelet packet transform to analyze signals both in time and frequency space, this paper researches the statistic property of non-Gaussian stationary noise and its signal structure.

该文利用小波包变换的时频局部分析能力，研究了非高斯分布平稳随机噪声的统计特性，揭示了非高斯噪声信号的信号结构。

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