基于数据自适应归一化高斯函数的信号逼近及其在语音处理中的应用

[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing Pub Date : 1992-03-23 DOI:10.1109/ICASSP.1992.225952

S. Qian, Dapang Chen, Ke-Shiu Chen

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引用次数: 26

摘要

提出了一种基于数据自适应归一化高斯函数的信号逼近方法。这种方法类似于传统的Gabor展开，但它更精确、更有效。最后对语音信号进行了数值仿真，验证了该方法的有效性。

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Signal approximation via data-adaptive normalized Gaussian functions and its applications for speech processing

A signal approximation via data-adaptive normalized Gaussian functions is presented. This approach resembles the traditional Gabor expansion, but it is more precise and efficient. Numerical simulations for the speech signal are included to demonstrate the effectiveness of the new scheme.<>

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[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing

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