共查询到20条相似文献,搜索用时 187 毫秒
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针对低信噪比(SNR)环境下传统方法对声信号降噪的局限性,提出了一种联合自适应阈值活动语音检测(VAD)算法和最小均方误差对数谱幅度估计(MMSE-LSA)的实时降噪算法。首先,在VAD算法中通过基于能量概率最大值的概率统计来对背景噪声进行估计,对得到的背景噪声进行实时更新并保存;然后,将实时更新的背景噪声作为MMSE-LSA的参考噪声,并对噪声幅度谱进行自适应更新,最后进行降噪处理。通过在真实场景中对四类声信号进行实验,结果表明,该算法在保证对低SNR声信号的实时处理的情况下,相较于传统MMSE-LSA算法,降噪信号的SNR能够提高10~15 dB,且不存在信号过减的情况,可应用于实际工程。 相似文献
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为了提高压缩感知中随机滤波器采样信号的重构性能,该文采用L1最小化重构算法对压缩信号进行重构。通过数值试验表明,对于随机滤波器采样的信号,L1最小化重构算法的重构效果优于正交匹配追踪算法的重构效果。 相似文献
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针对匹配追踪(matching pursuit,MP)算法在检测电能质量扰动信号时存在的计算量大、重构信号质量不佳的问题,利用混沌动态多种群粒子群优化(chaos dynamic multi-swarm particle swarm optimization,CDMSPSO)算法对MP算法进行优化,提出了CDMSPSO-MP算法。首先,CDMSPSO算法使用Logistic映射替代伪随机数更新种群,提高信号重构时搜索时频原子的随机性;然后,将种群划分为多个小规模种群并设置相应的重组期,增加信号重构时频原子的多样性;最后,以扰动信号与原子内积的绝对值作为CDMSPSO算法的适应度函数,替代MP算法的遍历计算,提升信号的重构速度。实验结果表明,CDMSPSO-MP算法有效提高了计算速度,减少了无关时频原子作为扰动信号分量的计算,提高了重构信号的质量。 相似文献
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在分析了经典的重构算法的不足之后,以小波变换的多孔算法电路为依据,提出了一种改进的解析迭代新算法,由信号的各个分解尺度上的小波变换的模极大序列和最大分解尺度上的离散逼近信号,通过迭代直接重构信号。该算法不需要进行小波反变换,也不需要对最大分解尺度上的离散逼近信号进行重采样,而且投影算子是解析形式的,克服了非解析形式投影算子计算量大、程序复杂等缺点。数值仿真试验证明了该算法信号重构的精度较高,收敛速度较快。 相似文献
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Michael Andrews 《Computers & Electrical Engineering》1983,10(1):29-40
Finite word length arithmetic roundoff noise in adaptive filter algorithms results in statistical variations in the filter weight vector about the infinite precision arithmetic weight vector. These roundoff errors may be modeled as a statistically non stationary driving noise affecting weight mean and covariance convergence. Mean and covariance expressions and bounds are desired for word lengths in fixed-point arithmetic by making use of multiplication roundoff error models. The adaptive filter algorithms consist of the LMS algorithm, the Widrow-Hoff LMS algorithm, pilot-vector algorithm and clipped vector algorithm. All of these algorithms can be implemented on-line and real-time. However, only the behavior of the LMS algorithm is reported here. The implementation of the adaptive filter algorithms in finite word length arithmetic is most evident in minicomputer, microprocessor, and dedicated digital signal processors for on-line real-time signal identification and parameter estimation in many disciplines. Radar signal processing, adaptive beam forming, acoustic signal identification, communication channel enhancement have a definite need for advanced filtering concepts. Our adaptive algorithms are typically employed in these filter configurations. These filters can also be employed in phase distortion equalizers. A particular advantage of these filters is that they can be trained to equalize a variety of distortions. Should a particular distortion scenario change in time, the filters can be made to easily adapt to the new problem. 相似文献
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细胞膜离子单通道电流十分微弱(PA级),用膜片钳技术测量离子电流往往淹没在强噪声背景中。目前,采用阈值检测方法恢复通道电流信号。但是,通道开放和关闭的电流阈值需要人为设定,并且阈值法在较低信噪比时失效。采用隐马尔可夫模型(HMM)重构离子单通道电流并估计模型参数。对离子通道HMM进行描述和分析;运用Baum-Welch迭代算法训练HMM并估计模型参数;利用Viterbi算法重构通道电流最佳状态序列。将HMM与阈值法进行比较,对不同信噪比和不同转移概率情况下HMM恢复算法进行计算机仿真。结果表明:HMM与阈值法相比,具有较强抗噪能力。在较低信噪比情况下,该模型恢复信号精度高,参数收敛速度快,且电流重构误差主要出现在状态突变点。 相似文献
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基于小波域HMM模型的自适应图像水印算法 总被引:1,自引:0,他引:1
An adaptive image watermarking algorithm based on HMM in wavelet domain is proposed. The algorithm is abstracted as follows: 1) the vector HMM model is employed to describe the statistical characteristic of image wavelet coefficients and the resulting HMM based detector achieves significant improvements in performance compared to the conventional correlation detector; 2) adaptive watermark embedding based on HVS analysis; 3) a novel embedding strategy which is optimized for the HMM tree structure is adopted; 4) the strategy of dynamical threshold is applied in watermark detection. High robust results are achieved against Stirmark attacks, such as JPEG compression, adding noise, median cut and filter. 相似文献
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An adaptive image watermarking algorithm based on HMM in wavelet domain is pro- posed.The algorithm is abstracted as follows:1)the vector HMM model is employed to describe the statistical characteristic of image wavelet coefficients and the resulting HMM based detector achieves significant improvements in performance compared to the conventional correlation detector; 2)adaptive watermark embedding based on HVS analysis;3)a novel embedding strategy which is optimized for the HMM tree structure is adopted;4)the strategy of dynamical threshold is applied in watermark detection.High robust results are achieved against Stirmark attacks,such as JPEG compression,adding noise,median cut and filter. 相似文献
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Trend analysis is an efficient tool for process monitoring and diagnosis. However, the performances of a trend-based diagnosis system depend on the reliability of the trends extracted from the signals. One challenge in trend analysis is to design algorithms able to adapt themselves to the varying conditions of background noise and artefacts occurring non-deterministically on a same signal. Moreover, while long term trends such as decreasing/increasing have been extensively studied other subtle changes such as slow drifts and step-like transients have received little attention. In this paper, an adaptive on-line trend-extraction method is presented. It extends a former algorithm based on a linear segmentation to filter the signal and extract trends. In this version, the tuning parameters are not set to a fixed value for a given signal but can self-adapt on-line according to an estimation of the noise variance. An increasing or decreasing trend is detected if the variations on the signal are significantly higher than the level of the background noise. An initialisation phase is proposed to automatically set the initial values of the parameters, making the algorithm a self-tuned algorithm with minimal user intervention.The method was evaluated on a set of simulated data with various levels of background noise. It was also applied on real physiological data recorded from babies hospitalised in a Neonate Intensive Care Unit. It showed improved performances compared to the non adaptive algorithm, whatever the level of noise corrupting the data. 相似文献
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回声消除一直是信号处理领域的热门研究方向,其中自适应滤波器是在回声消除问题中最为广泛应用的技术,但自适应滤波算法主要是在基于高斯噪声条件下的应用,而现实环境广泛存在着非高斯的噪声,这严重影响了基于L2范数的自适应噪声滤波算法的噪声消除性能。为解决回声消除方法对非高斯噪声的适用性问题,根据回声路径具有明显的稀疏系统特性,结合比例矩阵的设计思想以及符号算法(SA),提出一种改进的MIPNSA算法。该滤波算法既能很好地适应于不同的背景噪声,同时也在较大程度上增强了对稀疏系统的适应能力。仿真测试结果表明,在高斯噪声和非高斯噪声条件下,本算法比现有的一些算法的回声消除效果更佳。 相似文献
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基于小波域HMM模型的稳健多比特图像水印算法 总被引:12,自引:0,他引:12
稳健性是多比特图像水印的关键问题之一,提出了一种基于小波域隐马尔可夫模型(hidden Markov model,简称HMM)的多比特图像水印算法,该算法的主要特点为:(1) 利用向量HMM模型精确描述图像小波系数间的统计特性,基于此统计模型的水印盲检测系统较之传统的相关检测器,在性能上有显著的提升;(2) 结合视觉掩盖特性,自适应地调整水印嵌入强度,使之在一定的嵌入强度下,视觉主观失真较小;(3) 提出了一种适合隐马尔可夫模型树型结构的多比特数据优化嵌入策略和最大似然检测.数值仿真结果表明,该算法可以较好地利用图像小波域的低频子带以实现较大容量图像水印的嵌入,并在抵抗Stirmark平台攻击,如JPEG压缩、加噪、中值滤波和线性滤波等方面具有很强的稳健性. 相似文献
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双麦克风噪声抵消应用中,由于交叉串的存在,传统自适应算法降噪性能受到很大的影响。为了提高双麦克风算法降噪性能,使用两级自适应滤波系统消除交叉串扰问题。为提高自适应滤波器收敛性能,采用主从结构LMS算法自适应调节步长因子。同时为了适合窄带处理算法,将输入信号进行子带分析预处理,对每个子带独立进行抗交叉串绕自适应处理,将各子带增强信号合并得到增强语音信号。实验结果表明,该方消噪量大,语音损伤小,语音增强效果显著。 相似文献