谐波线谱簇干扰自适应抵消器

对于舷侧阵声呐本地干扰抵消技术,优良参考信号的抬取以及数据融合是关键.木文首先分析舷侧阵声呐使用频段内自噪声的频率分布特性,然后提出谐波线谱簇干扰抵消器的概念.文献1中给出单频线带干扰抵消器的理论分析,本文给出多频线谱于扰抵消器的理论分析.基于陷波滤波器品质因素的表达式,给出恒Q值线谱干扰抵消器的设计方法.同时提出一种性能优良的实现谐波线谱簇合成的方法.计算机仿真结果以及海试数据分析结果令人满意.     

基于模式搜索的自适应干扰抵消器算法的研究

为了减小同址干扰对接收机性能的影响,设计了一种基于正交矢量合成的自适应干扰抵消器;根据其中控制单元提取出的数据的特点,提出了将模式搜索算法(PSA)作为控制器算法,并对其进行了改进;利用实际测量的数据进行了仿真分析,结果表明,相比于PSA算法、模拟退火算法、遗传算法,改进后的PSA算法具有更快的收敛速度,同时收敛精度相差无几;最终的实现结果也证明了该方法可满足性能要求。     

视听系统声干扰的自适应抵消

对一个用语音遥控的视听系统而言,视听系统本身所发出的声音常常造成语音识别的错误,本文所采用的自适应声干扰低消技术能有效地降低这种声干扰,基于自适应声干扰抵消最佳性能的分析,导出了抵消性能与权系数的个数以及混响时间的表达式,并实时地实现了带有１０２４个权系数的自适应声干扰抵消系统。在一般居室中,声干扰的抵肖可达２６ｄＢ。     

一种采用脉冲串的自适应有源干扰抵消器

在许多应用中，周期性干扰是由旋转的机械设备所产生的。一个周期性信号可以与一个特殊形式的周期性的脉冲串完全相干。本文提出了一种采用脉冲串的自适应有源噪声抵消器(AANC)来抵消周期性干扰，这种抵消器产生一个与干扰信号相同步的周期性的单位脉冲串作为参考输入。将这种有源噪声抵消器和Delayed-X LMS算法相结合，可以大大地减小运算量，并且也可以保证良好的收敛特性。理论分析和计算机仿真验证了本文的结果。     

主瓣约束自适应旁瓣抵消器的实验研究

空间预滤波加无约束自适应噪声抵消器构成了一种主瓣约束的自适应旁瓣抵消器。这种自适应旁瓣抵消器由于实现了保持主瓣方向以及主瓣形状的导数约束,具有较好的主瓣保持性能,且结构简单,便于工程实现。本文在原有理论研究的基础上,着重从实验方面研究这种自适应旁瓣抵消器的主瓣保持和旁瓣抵消性能。设计并构造了一个实验系统,该系统利用一种新的空间预滤波结构,使其更宜于工程实现。进行了水池和海上试验,详细考察了输入信噪比、信号干扰比、信号与干扰带宽和自适应步长因子等参数对系统性能的影响。取得的结果证实了理论分析的正确性。     

改善线性调频脉冲干扰自适应抵消效果的一种新方法

针对线性调频脉冲（ＬＦＭ）干扰自适应抵消的跟踪问题,提出了一种新的变采样率方法,根据ＬＭＳ算法响应ＬＦＭ输入的稳态权特性解释了变采样率能改善自适应算法跟踪能力的原因,并对相同情况下固定采样率和变采样率的性能进行了仿真比较．     

自适应格形联合滤波噪声抵消器及优化步长

自适应噪声抵消方法(ANC)能有效地增强被加性噪声干扰的信号。鉴于传统的采用LMS横向滤波器(TF)的ANC(TFANC)有其缺点,本文研究了采用格形联合滤波器(LF)的ANC(LFANC),证明了它具有基本上不依赖于输入的优异收敛性能。另外,针对前人工作的不足,我们从理论上着重研究导出了LFANC的失调的解析表达式并进行了实验验证,从而得到失调随滤波器级数呈指数增长的重要结论。我们还成功地将优化步长用于多级LF,这样就能在几乎不增加运算量的前提下大大加快LF的收敛,将以上方法用于对真实含噪语音的处理,取得了较好的效果。     

应用于拖线阵声呐的一种自适应旁瓣干扰抵消器的性能分析

拖线阵声呐要求在全方位上对强干扰进行抑制,但当强干扰是宽带并与信号方向偏离较大时,自适应干扰抵消器的性能会受到限制。本文对一种具有抽头延迟线结构的部分自适应旁瓣抵消器(PASC)在用于抑制大角度宽带干扰时的性能进行了分析。数值结果表明,在合理选取参数和结构的情况下,这种PASC在用来抵消一定带宽和偏离角的强干扰时,具有较好的抵消性能。     

维纳滤波的多项式逼近与自适应格式滤波器

最近,自适应格式滤波在各个方面得到了广泛的应用。与横向滤波器相比,它具有一些突出的优点。本文从维纳滤波的多项式逼近出发引出Szego多项式,阐明从横向滤波器到格式滤波器的自然过渡,进而分析讨论了格式滤波器的主要特性。最后简单介绍两种自适应格式算法。     

几种自适应IIR陷波器的复数算法及其应用

在自适应IIR陷波器实数算法的基础上,本文提出了三种基于梯度的自适应IIR陷波器的复数算法,并进行了仿真比较。结果表明,这三种复数算法均可检测复信号,并估计信号频率,其中\"改进的\"简化格型IIR陷波器复数算法收敛速度快、低信噪比下稳定性能好。湖上试验表明该算法不仅实时性好,而且在低信噪比下的检测效果令人满意。     

Real-time blind deconvolution of retinal images in adaptive optics scanning laser ophthalmoscopy

With the use of adaptive optics (AO), the ocular aberrations can be compensated to get high-resolution image of living human retina. However, the wavefront correction is not perfect due to the wavefront measure error and hardware restrictions. Thus, it is necessary to use a deconvolution algorithm to recover the retinal images. In this paper, a blind deconvolution technique called Incremental Wiener filter is used to restore the adaptive optics confocal scanning laser ophthalmoscope (AOSLO) images. The point-spread function (PSF) measured by wavefront sensor is only used as an initial value of our algorithm. We also realize the Incremental Wiener filter on graphics processing unit (GPU) in real-time. When the image size is 512 × 480 pixels, six iterations of our algorithm only spend about 10 ms. Retinal blood vessels as well as cells in retinal images are restored by our algorithm, and the PSFs are also revised. Retinal images with and without adaptive optics are both restored. The results show that Incremental Wiener filter reduces the noises and improve the image quality.     

The effect of Laplacian filter in adaptive unsharp masking for infrared image enhancement

Image processing, in particular image enhancement techniques have been the focal point of considerable research activity in the last decade. With the aid of an existing image enhancement technique, adaptive unsharp masking (AUM), we propose a novel kernel to be used in AUM filtering in order to enhance discontinuities which occur on the edges of targets of interest in infrared (IR) images. The proposed method uses an adaptive filter approach where an objective function is minimized by using descent algorithms. The output IR image has better sharpness and contrast adjustment for the detection of targets in terms of objective quality metrics. Hence, the proposed method ensures that the edges of the targets in IR images are sharper and that the quality of contrast adjustment has its optimum level in terms of peak signal-to-noise ratios.     

Neural network processing for adaptive line enhancement

This paper describes the inverstigation devoted to establish suitable weights in a feed-forward neural network realizing the narrow-band filtering map in the case of adaptive line enhancement(ALE) by the utility of the optimum common learning rate back propagation (OCLR BP) algorithm. It is found that a feed-forward network with 64 linear input and output neurons, and 8 odd sigmoid neurons in the hidden layer, i.e. an (64→8→64) architecture, could establish the specific input-output function in the case of relatively low signal-to-noise radio. Only is an input signal consisting of mixed periodic and broad-band components available to the network system. After learning, both the \"fanning-in-connection patterns\", each of which consists of weights fanning into a hidden-neuron From all the outputs of input-neurons, and the \"fanning-out-connection patterns\", each of which consists of weights fanning out from a hidden-neuron to all the inputs of output-neurons, are tuned to the periodic signals. The nonline     

On implementation of adaptive bilinear filters for nonlinear active noise control

In this technical note, the simplified diagonal-structure bilinear filtered-X least mean square (SDBFXLMS) and channel-reduced diagonal-structure bilinear filtered-X least mean square (CRDBFXLMS) algorithms are proposed. Computational complexity for each proposed algorithm is analyzed to show the significant computational reduction in comparison with the diagonal-structure bilinear FXLMS (DBFXLMS) algorithm. For L=15$L=15$ (memory length of the bilinear filter), P=2$P=2$ (the corresponding number of the diagonal channels for the SDBFXLMS algorithm is L+2P=19$L+2P=19$ and the corresponding number of the diagonal channels for the CRDBFXLMS algorithm is 2P=4)$2P=4)$, and M=64$M=64$ (memory length of the secondary path estimate), the SDBFXLMS algorithm achieves 45% and 40% reduction of multiplications and additions, respectively, while the CRDBFXLMS algorithm acquires 78% reduction of multiplications and 76% reduction of additions. Computer simulations validate the satisfied control performances of the proposed algorithms.     

Performance of underwater adaptive array including mutual coupling effects

In this paper, the mutual coupling effects on the performance of underwater adaptive arrays are analyzed. This study manifests the discrepancies between cases of considering and ignoring the mutual coupling effects. The least mean square (LMS) based adaptive array is utilized to illustrate the mutual coupling effects. Numerical examples show that the performance of an underwater adaptive array can be improved as mutual coupling effects are considered. The consideration of mutual coupling effects is necessary in analyzing underwater adaptive arrays.     

一种新的方向滤波器组及其在图像去噪中的应用

通过将二维棋盘形滤波器对和二维余弦调制滤波器组相结合,构造了具有方向和频率选择性的新的方向滤波器组。本文中,我们首先设计了具有45度和135度方向的二维棋盘形滤波器对。通过棋盘形滤波器对,输入图像首先被分解为两幅图像。然后,二维余弦调制滤波器组被分别应用到每幅图像。这种结构等效于一个冗余比为2的方向滤波器组。新的滤波器组具有良好的方向和频率选择性。作为新滤波器组的一个应用,我们把双重局部维纳滤波算法和新的方向滤波器组相结合,提出了一种新的图像去噪算法。实验结果表明：对于具有丰富纹理的图像,提出的算法获得了明显的去噪性能改善。     

Speech dereverberation method based on spectral subtraction and spectral line enhancement

Speech signals recorded with a distant microphone usually are interfered by the spatial reverberation in the room, which severely degrades the clarity and intelligibility of speech. A speech dereverberation method based on spectral subtraction and spectral line enhancement is proposed in this paper. Following the generalized statistical reverberation model, the power spectrum of late reverberation is estimated and removed from the reverberation speech by the spectral subtraction method. Then, according to the human auditory model, a spectral line enhancement technique based on adaptive post-filtering is adopted to further eliminate the reverberant components between adjacent speech formants. The proposed method can effectively suppress the spatial reverberation and improve the auditory perception of speech. The subjective and objective evaluation results reveal that the perceptual quality of speech is greatly improved by the proposed method.     

Random-valued impulse noise removal by the adaptive switching median detectors and detail-preserving regularization

This paper firstly proposes an adaptive non-local switching median filter. Then, a two-phase scheme is presented to remove the random-valued impulse noise. In the first phase, the adaptive switching median filter or the adaptive non-local switching median filter is used to identify the pixels which are likely to be the noise candidates. In the second phase, only the noise candidates’ values are restored by a detail-preserving regularization method. Simulation results show that the proposed method is significantly superior to some of the state-of-the-art methods.     

Performance simulation of an adaptive optics system with liquid crystal corrector under closed-loop and open-loop control

The adaptive optics system (AOS) often operates in a discrete sampling process with finite closed-loop frequency. Reconstruction, detection, and time lag induced errors are the main correction errors of the system. An AOS that is based on a liquid crystal (LC) benefits from the LC’s high correction precision, thus the reconstruction error can be ignored. The primary error will be induced by the time lag from the time of detection to the time of compensation. In this paper, some theoretical simulations are introduced in order to evaluate the correction precision of AOS with an LC corrector. The main purpose is to compare the correction precision between the open-loop and closed-loop control. We attempt to find a method to ascertain the exact precision of the open-loop control and show whether it improves the correction precision. The conclusion is thus reached that the actual error rejection bandwidth for the closed-loop was lower than the −3 dB error rejection bandwidth measured in practice. The increased refresh frequency of the open-loop control can improve the imaging performance to nearly −3 dB bandwidth of the detector measured, which is the maximum possible bandwidth due to the time lag.     

A robust adaptive hybrid feedback cancellation scheme for hearing aids in the presence of outliers

It has been demonstrated that the Filtered-x Wilcoxon LMS (FxWLMS) based adaptive filter mitigates the effect of the outliers acquired by the microphone signal of hearing aids by minimizing the Wilcoxon norm and hence shows better cancellation performance than the existing Filtered-x LMS (FxLMS) algorithm. The prediction error method based adaptive feedback canceller (PEMAFC) reduces the bias present in the estimate of the feedback path due to the continuous adaptive filtering (CAF). However, the impulse response of the measured feedback path is close to zero for the first many samples due to the delay introduced by ADC converters and then contains few significant values, which results in slow convergence rate when an adaptive filter is used to model the same. To overcome this limitation, we propose a proportionate normalized WLMS (PNWLMS) algorithm based PEMAFC (P-PNWLMS) for feedback cancellation in hearing aid in the presence of outliers. Further, with an objective to improve the convergence rate and performance accuracy simultaneously, this paper proposes a novel convex PNWLMS (CPNWLMS) algorithm which incorporates convex combination of PNWLMS and WLMS algorithms. The weight update equations are derived for PEMAFC trained by PNWLMS (P-PNWLMS) and CPNWLMS (P-CPNWLMS) algorithms respectively. The results of the simulation study show improved performance of the proposed CPNWLMS based adaptive filter over its component filters.