基于ACF和AMDF的基音检测改进算法

自相关函数法和平均幅度差函数法是基音周期检测的两种常用方法,两者具有独立且相似的统计特性。在讨论了传统基音周期检测算法及其缺点后,提出了综合应用ACF和ANDF函数进行基音检测的算法。该算法简单可行,性能优于一般传统时域基音周期检测算法。从仿真结果可以看出,对于含噪语音信号,该算法具有较强的抗噪能力。     

基于小波变换的语音基音周期检测

语音信号是一种非平稳信号,基音周期是语音信号最重要的参数之一,传统的基音检测方法存在一些缺陷.小波变换鲁棒性强、能很好地反映信号的时频特性,非常适合处理非平稳信号.为准确提取基音频率,提出了一种基于小波变换的基音周期检测方法.检测前在小波域上用Teager能量算子分离出语音信号的浊音段,然后对浊音段采用空域相关函数降噪...     

基于同态滤波的基音检测算法

噪声环境下的基音检测在语音信号分析和识别中占有重要地位.文中阐述了一种新的基于同态滤波和经典自相关函数法的基音周期检测算法.实验表明,该方法是可行的,与传统方法相比鲁棒性好,特别适用于信噪比较低的情况.     

基于Teager能量算子和空域相关函数的基音检测算法

结合Teager能量算子和空域相关函数,提出了一种有效的基音周期检测方法。检测前在小波域上用Teager能量算子对语音信号进行清浊音判决,对浊音段采用空域相关函数提取基音周期。实验表明,与传统的小波变换算法和自相关法相比,该方法鲁棒性好,具有更高的准确性。     

基干Teager能量算子和空域相关函数的基音检测算法

结合Teager能量算子和空域相关函数,提出了一种有效的基音周期检测方法.检测前在小波域上用Teager能量算子对语音信号进行清浊音判决,对浊音段采用空域相关函数提取基音周期.实验表明,与传统的小波变换算法和自相关法相比,镇方法鲁棒性好,具有更高的准确性.     

基于LPC的藏语语音基音周期的检测分析

基音周期是语音信号的重要参数,提取藏语语音基音周期为藏语语音识别和藏语语音合成奠定很重要的基础。这里在分析藏语发音特点的基础上进行基于LPC的藏语语音基音周期提取算法的分析,实践表明,该方法更加符合小信噪比藏语音信号基音周期和提取。在传统LPC分析方法的基础上结合自相关法和倒谱法,分析计算平均相对误差,总结出了符合藏语语音特点的特征提取算法。     

一种语音更改技术的研究与实现

基于时域基音同步叠加算法完成了对语音信号的更改。首先求出语音信号的基音周期,接着对语音信号进行基音标注,然后对基音周期进行更改,最后,将语音信号按照更改后的基音周期基于时域基音同步叠加算法进行语音合成。实验表明,语音更改方法可得到很好的效果。     

基于CEP和LPC谱提取语音信号基音周期的方法

在语音信号分析中,只有分析出可表示语音信号本质特征的参数,才有可能利用这些参数进行高效的语音通信、语音合成和语音识别等处理.因此对语音信号采用CEP和LPC谱提取语音信号基音周期的异同进行了研究,并采用Matlab实现了仿真分析.从中可以看出,LPC谱估计基音周期的算法运算量较大,而CEP谱算法更直观,且在少部分情况下基音峰会变得更突出一些,CEP谱具有更加广阔的应用前景.     

基于小波变换的清浊音分类及基音周期检测算法

该文提出了一种基于小波变换的鲁棒性基音周期检测方法。检测前在小波域上用Teager能量算子对语音信号进行清浊音判决,对浊音段采用空域相关函数提取基音周期。实验表明,与传统的小波变换算法和自相关法相比,该方法鲁棒性好,具有更高的准确性。     

基于ACF的基音检测改进算法

自相关函数法是基音周期提取中一种简单而有效的检测算法,针对传统的自相关函数法在低信噪比环境下鲁棒性较差的问题,提出一种改进的基音周期提取算法。该算法通过谱减法对语音信号降噪,随后进行端点检测,并提取元音的主体,在自相关函数的基础上进行改进,对元音主体及过渡区间进行基音检测。实验结果表明,该算法具有较高的准确率,与传统自相关检测算法相比,鲁棒性明显提高。     

一种新的FSK最佳相干解调器

本文讨论在信号各频率振幅受到的衰减不一致并存在有色加性高斯噪声(IGDF-ACGN)信道条件下,FSK信号的最佳相干解调问题。基于矢量表示系统模型的方法,导出了最佳解调器的结构。从理论分析和计算机模拟实验结果都证明了所导得的最佳解调器,不仅在IGDF-ACGN信道条件下是最佳的,而且在加性高斯白噪声(AWGN)信道条件下也是最佳的。文中还导出了相应的误码率公式,给出了误码率数值计算和计算机模拟曲线。     

新型MFSK最佳相干解调器

本文推广了作者在1999年提出的方法和结论[1],讨论了在信号各频率振幅受到的衰减不一致并存在有色加性高斯噪声(IGDF-ACGN)信道条件下,M进制FSK(MFSK)信号的最佳相干解调问题。导出了最佳解调器的结构,说明了该解调器中有关参数的估计方法,以及实现时遇到的矢量、矩阵运算的有关快速算法。从理论和计算机模拟实验两方面说明了所导得的最佳解调器,不仅在IGDF-ACGN信道条件下是最佳的,而且在加性高斯白噪声(AWGN)信道条件下也是最佳的。文中给出了误码率的计算机模拟曲线。     

Optimal coherent detection of FSK signals with imbalance amplitudes in the presence of colored gaussian noise

The problem of optimal coherent detection of frequency-shift keying (FSK) signals transmitted over an additive colored Gaussian noise channel with imbalance gains in different frequencies (IGDF-ACGN channel) is studied. The structure of the optimal coherent detector is derived. Theoretical analysis and computer simulation results show that the detector is optimal in either additive colored Gaussian noise environment or additive white Gaussian noise environment.     

Results on Discrete-Time, Decision-Directed Integrated Detection, Estimation, and Identification

New results are presented for symbol-by-symbol detection with decision-directed tracking of colored channel disturbances. Recursive sampled-data algorithms are shown for Maximum A Posteriori Probability of detection under colored additive and multiplicative Gaussian noises along with white Gaussian noise. Preliminary evaluation of the algorithms via Monte Carlo simulation shows good performance compared to standard white-noise only algorithms.     

分形方法用于有噪图像边缘检测的研究

本文研究了加性高斯白噪声对于基于离散分数布朗随机场模型图像分形维数估计的影响，并将分形方法用于图像边缘检测，指出在加性高斯白噪声的情况下，分形方法用于图像边缘检测较之经典的基于梯度运算的边缘检测方法有好的抗噪性能，同时又能检测比较丰富的图像边缘细节。     

基于子空间旋转不变性的加性有色噪声中谐波频率的估计

噪声中的谐波恢复问题是信号处理领域的一个典型问题,在众多领域中有着广泛的应用。本文主要研究加性有色噪声中谐波频率的估计问题,提出了一种基于子空间旋转不变性的谐波频率的高分辨率估计方法。利用观测信号的自协方差函数构造了一个协方差矩阵,通过对协方差矩阵的特征值进行理论分析,结合子空间旋转不变性,得到了加性有色噪声中谐波的频率和协方差矩阵之间的一种内在联系。利用这个性质可以估计加性有色噪声中谐波的频率。本文方法对于有色噪声的模型无任何假设,而且对于噪声的分布也没有限制,对于高斯和非高斯有色噪声都适用。仿真实验验证了本文所提算法的有效性。      

A general likelihood-ratio formula for random signals in Gaussian noise

It is shown that the likelihood ratio for the detection of a random, not necessarily Gaussian, signal in additive white Gaussian noise has the same form as that for a known signal in white Gaussian noise. The role of the known signal is played by the casual least-squares estimate of the signal from the observations. However, the "correlation" integral has to be interpreted in a special sense as an Itô stochastic integral. It will be shown that the formula includes all known explicit formulas for signals in white Gaussian noise. However, and more important, the formula suggests an "estimator-correlator" philosophy for engineering approximation of the optimum receiver. Some extensions of the above result are also discussed, e.g., additive finite-variance, not necessarily Gaussian, noise plus a white Gaussian noise component. Purely colored Gaussian noise can be treated if whitening filters can be specified. The analog implementation of Itô integrals is briefly discussed. The proofs of the formulas are based on the concept of an innovation process, which has been useful in certain related problems of linear and nonlinear least-squares estimation, and on the concept of covariance factorization.     

The optimum constant false alarm probability detector for relatively coherent multichannel signals in Gaussian noise of unknown power

In this paper, the method of "most powerful similar tests" is used to obtain the optimum (largest probability of detection) constant false alarm probability detector for multichannel signals received in the presence of additive Gaussian noise of unknown power. The signals are assumed to contain a common random phase angle, and hence are relatively coherent over the multiple channels. The noise is assumed to be correlated from channel to channel. The performance of the optimum detector is calculated. Finally, for illustrative purposes, the technique is applied to the detection of a signal in the presence of a jammer, and to the detection of a single channel signal in white and colored noise of unknown power.     

Detection of a known signal in colored Gaussian noise---A new coordinate approach (Corresp.)

The classical problem of detecting a known signal in additive colored Gaussian noise on a finite interval is considered by using as "coordinates" (observables) the inner products formed between the received waveform and the elements of a simply constructed complete set of functions defined on the observation interval. Results of the Karhunen-Loève (K-L) approach are thereby obtained without the K-L expansion or any appeal to results from integral equation theory.     

Single-user detectors for multiuser channels

Optimum decentralized demodulation for asynchronous Gaussian multiaccess channels is considered. It is assumed that the receiver is the destination of the information transmitted by only one active user, and single-user detectors that take into account the existence of the other active users in the channel are obtained. The problem considered is one of signal detection in additive colored nonGaussian noise, and attention is focused on one-shot structures where detection of each symbol is based only on the received process during its corresponding interval. Particular emphasis is placed on asymptotically optimum detectors for weak interferers, for CDMA (code-division multiple-access) signature waveforms with long spreading codes, and for low background Gaussian noise level