结果病态嗓音和正常嗓音的频谱高端相对信噪比存在显著差异。
Results the relative signal-to-noise ratio of the pathologic voice on high frequency differed significantly from that of the normal voice.
结果表明男女正常嗓音的频域相对信噪比均呈一个稳定的分布。
The result indicated that the relative harmonics to noise ratios of the normal voice for both male and female have a stable distribution.
结果病态嗓音和正常嗓音的频谱高端相对信噪比存在显著差异。
Results the relative signal-to-noise ratio of the pathologic voice on high frequency differed significantly from that of then...
目的通过研究早期病理嗓音的相对信噪比变化，寻找检测早期喉疾病的方法。
Objective to detect laryngeal diseases early by studying the relative signal-to-noise ratio changes in the early pathologic voice.
在较低信噪比情况下，基于语音信号的短时相对自相关序列的短时平均幅度的端点检测能够获得较高的检测精度。
The endpoint detection based on short-time average magnitude of speech signals relative autocorrelation sequences can be detected in high accuracy under the low signal-to noise ratio.
计算机仿真与光学扫描实验表明，该方法具有认证过程相对简单、解码图像信噪比高、成本低和防伪性能好等优点。
Computer simulations and optical scanning experiments show that the presented technique has advantages of the simple authentication process, high PSNR, inexpensive cost and good security.
针对图像序列中红外弱小目标的检测与跟踪中遇到的难点，即信噪比低、帧间相对位移小等问题，提出一种基于小波提升框架及小波能量的目标检测算法。
To solve the difficulties in dim target detection, such as low SNR and small-scale displacement, a new automatic target detection algorithm based on lifting scheme and wavelet energy is proposed.
相对于正常语音来说，耳语音在公共场合的信噪比较低，而且没有基音周期，共振峰不明显，所以耳语音增强具有一定的难度。
The SNR in public environment of whispered speech is lower than normal speech and the former hasn't pitch period and its formants are not obvious, so whispered speech enhancement is harder.
模型研究显示：对于储层研究，信噪比不小于2的地震资料是相对可靠的。
Model study showed that when SNR is no less than 2, the seismic data is more reliable.
结果证明，相对于其他方法，高次逼近法去噪效果良好，得到的信噪比更高。
The result verifies that the high order approximation method offers better denoising effect and higher signal to noise ratio.
实验结果表明，相对于传统算法，本文检测法检测结果信噪比更高，目标更加完整，运行速度平均提高了22%。
The results show that the objects extracted by the proposed method with higher SNR and the processing time decreases 22% contrasting to traditional algorithm.
实验结果表明，相对于传统算法，本文检测法检测结果信噪比更高，目标更加完整，运行速度平均提高了22%。
The results show that the objects extracted by the proposed method with higher SNR and the processing time decreases 22% contrasting to traditional algorithm.
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