共查询到8条相似文献,搜索用时 62 毫秒
1.
针对LPCC易受噪声干扰和不能反映人耳听觉特性的缺点,提出了新的抗噪声特征,实验表明,在各种信噪比(SNR)环境中,该方法的精度高于线性预测倒谱系数(LPCC)和美尔倒谱系数(MFCC). 相似文献
2.
3.
梅尔频率倒谱系数(Mel Frequency Cepstrum Coefficient,MFCC)是一种符合人耳听觉特征,并与频率呈非线性对应关系的频谱特征,广泛应用在语音识别、音频特征分析等方面.对于目前广泛使用的通过单一特征进行音频分类的方法,存在分类准确度低、处理速度慢等方面的不足,提出了基于梅尔频率倒谱的音频分... 相似文献
4.
5.
6.
7.
为了实现非协作环境下的通信信号信噪比估计,本文在功率谱分析的基础上,提出了一种基于功率谱差分的信噪比盲估计算法,并将其与传统的基于奇异值分解的信噪比盲估计算法进行了比较。理论与仿真结果表明,与传统方法相比,本文提出的算法不但复杂度低,而且在低信噪比情形下仍具有较高的估计精确度和稳健性。 相似文献
8.
Seyed Ali Mohajeran Ghosheh Abed Hodtani 《International Journal of Communication Systems》2020,33(14)
In this paper, the power allocation problem in a wireless sensor network (WSN) with binary distributed detection is considered. It is assumed that the sensors independently transmit their local decisions to a fusion center (FC) through a slow fading orthogonal multiple access channel (OMAC), where, in every channel, the interferences from other devices are considered as correlated noises. In this channel, the associated power allocation optimization problem with equal power constraint is established between statistical distributions under different hypotheses by using the Jeffrey divergence (J‐divergence) as a performance criterion. It is shown that this criterion for the power allocation problem is more efficient compared to other criteria such as mean square error (MSE). Moreover, several numerical simulations and examples are presented to illustrate the effectiveness of the proposed approach. 相似文献