Two-stage interference immune blind equaliser which exploitscyclostationary statistics

Since cyclostationarity is inherent in many man-made signals, there is much to be gained in the signal processing and communication areas if this property is properly recognised and exploited. In particular, the authors propose a novel two-stage scheme which exploits second-order cyclostationary statistics for co-channel interference removal and blind equalisation. The first stage adopts the blind adaptive (BA) FRESH filter proposed by Zhang, to remove co-channel interference and channel noise. The second stage is based on a blind equalisation algorithm, proposed by Tong, which operates on the filtered cyclic signal to remove intersymbol interference. Simulation studies have demonstrated that this two-stage blind equalisation scheme has a fast rate of convergence and excellent performance in a high SNR environment     

Reduced-complexity equaliser for nonlinear channels

The generalised cerebellar model arithmetic computer (GCMAC) network is applied to the problem of adaptive equalisation of nonlinear channels. The GCMAC-based equaliser is compared with other well-known structures such as the Volterra filter and the multi-layer perceptron. The results obtained show the effectiveness of the proposed structure for compensating strong nonlinearities     

Block-based fuzzy step size nlms algorithms for subband adaptive channel equalisation

Judicious selection of the step size parameter is crucial for adaptive algorithms to strike a good balance between convergence speed and misadjustment. The fuzzy step size (FSS) technique has been shown to improve the performance of the classical fixed step size and variable step size (VSS) normalised least mean square (NLMS) algorithms. The performance of the FSS technique in the context of subband adaptive equalisation is analysed and two novel block-based fuzzy step size (BFSS) strategies for the NLMS algorithm, namely fixed block fuzzy step size (FBFSS) and adaptive block fuzzy step size (ABFSS) are proposed. By exploiting the nature of gradient noise inherent in stochastic gradient algorithms, these strategies are shown to substantially reduce the computational complexity of the conventional FSS technique without sacrificing the convergence speed and steady-state performance. Instead of updating the step size at every iteration, the proposed techniques adjust the step size based on the instantaneous squared error once over a block length. Design methodology and guidelines that lead to good performance for the algorithms are given.     

New automatic equaliser employing modulo arithmetic

The limitations of present automatic and adaptive equalisers stem from the use of feedforward transversal filters. These drawbacks may be obviated by using a feedback transversal filter, the inverse filter, but this is only suitable for limited use since it can be an unstable circuit. It is shown that modulo arithmetic may be used in the inverse filter to eliminate completely the possibility of instability, and a very simple automatic or adaptive equalisation system is presented. Some interesting properties of the modulo inverse filter are included.     

基于局部统计信息的模糊选择滤波算法

提出了一种基于局部统计信息的模糊选择滤波算法，该算法的输出是sigma滤波器与多级中值滤波器滤波结果的加权复合，其权值则是通过对图像中局部统计信息的推理得到的。因此，该算法能够根据图像的具体情况自适应地进行滤波。试验表明，本算法能够有效滤除图像中不同种类的噪声，并具有很好的细节保护能力。     

一种新的图像去噪混合滤波方法

为了去除图像中混入的脉冲噪声和高斯噪声,提出了一种基于自适应中值滤波和模糊加权均值滤波的混合滤波方法.该方法首先进行噪声检测把受高斯型噪声污染的像素和受脉冲型噪声污染的像素区别开来,然后对受高斯噪声污染的像素采用模糊加权均值滤波算法,而对受脉冲噪声污染的像素则采用改进的中值滤波算法进行去噪.仿真结果证明,该方法更具有实用性和有效性.     

Adaptive Fuzzy Filtering for Artifact Reduction in Compressed Images and Videos

A fuzzy filter adaptive to both sample's activity and the relative position between samples is proposed to reduce the artifacts in compressed multidimensional signals. For JPEG images, the fuzzy spatial filter is based on the directional characteristics of ringing artifacts along the strong edges. For compressed video sequences, the motion compensated spatiotemporal filter (MCSTF) is applied to intraframe and interframe pixels to deal with both spatial and temporal artifacts. A new metric which considers the tracking characteristic of human eyes is proposed to evaluate the flickering artifacts. Simulations on compressed images and videos show improvement in artifact reduction of the proposed adaptive fuzzy filter over other conventional spatial or temporal filtering approaches.      

低轨卫星信道自适应模糊估计算法

针对功率控制,提出一种利用模糊规则的自适应LMS信道估计算法,通过将信道增益大小和前后变化值的大小划分为若干模糊集,建立将自适应算法和经验值相结合的自适应滤波器,使算法具有对低轨信道时变特性一定的适应性。仿真结果表明了算法的有效性。     

Efficient IQ filter structure for use in adaptive equalisation

A method is presented for reducing the implementation cost of a complex digital filter structure such as that used for IQ processing in adaptive equalisation. It is shown that the number of real filter sections required can be reduced from four to three at the expense of an increase in external addition stages from two to three (or five if coefficient additions are included). The approach is applicable to both LTE and DFE structures and results in savings which approach 25% for most practical cases     

Adaptive path selective fuzzy decorrelating detector under impulsive noise for multipath fading CDMA systems

This letter proposes a novel adaptive path selective fuzzy decorrelating (APSFD) detector for direct-sequence code- division multiple-access (DS-CDMA), systems with time-varying multipath fading channels under impulsive noise. The proposed detector combines adaptive path selective decorrelating (APSD) detector with a fuzzy median filter which is based on fuzzy rank ordering of samples to eliminate the effect of impulsive noise. Simulation results clearly show that the proposed detector eliminates the effect of impulsive noise and improves the performance of APSD detector under high impulsive noise.     

EMCCD图像自适应模糊中值滤波算法研究

针对电子倍增CCD（EMCCD）图像噪声密度随着增益的变化而变化,提出了一种基于噪声点检测的自适应模糊中值滤波算法。该算法由模糊滤波模块和自适应模块两部分组成。首先,该算法对滤波窗口内的中心点进行噪声检测;然后对检测为噪声的像素点引入双阈值,并根据引入的阈值和滤波窗口内的中值建立噪声点的模糊隶属函数,根据模糊隶属函数对噪声点进行滤波处理后输出;最后采用自适应模块调整待处理图像的像素。仿真及实验结果表明,新算法不仅能够有效地将图像中的噪声去除,而且很好地保护了图像中的细节和边缘,PSNR比传统的自适应中值滤波算法平均提高了15 dB以上;该算法在低噪声密度情况下性能明显好于其他中值滤波器,在高噪声密度情况下性能也比较稳定。     

Complex fuzzy adaptive filter with LMS algorithm

A fuzzy adaptive filter is constructed from a set of fuzzy IF-THEN rules that change adaptively to minimize some criterion function as new information becomes available. This paper generalizes the fuzzy adaptive filter based on least mean squares (LMS) to include complex parameters and complex signals. The fuzzy filter as adaptive equalizer is applied to quadrature amplitude modulation (QAM) digital communication with linear complex channel characteristics     

基于三维轴距的图像去噪算法

图像去噪是图像处理邻域的重要课题,该文在3维直方图的基础上定义图像的3维轴距,分析无噪声及椒盐噪声影响下图像3维轴距的分布特点,提出基于3维轴距的去噪算法。算法首先对图像进行边沿扩展,再利用3维轴距来检测噪声,最后用非噪声中值滤波来消除噪声。仿真比较了3维轴距去噪算法与中值滤波、自适应开关中值、快速自适应均值滤波、修正方向加权中值滤波和自适应模糊开关中值滤波算法的去噪性能,结果证明该文算法的有效性。     

基于模糊理论的自适应联邦滤波算法研究

针对先验噪声统计特性与实际不符引起卡尔曼滤波精度下降的情况,提出了一种基于模糊自适应联邦卡尔曼滤波方法。算法基于模糊推理思想通过理论残差与实际残差的比值来对观测噪声协方差阵进行加权调整,实现对观测噪声统计特性的实时跟踪,在此基础上,利用信息分配因子对各子滤波器及主滤波器输出进行加权,得到滤波器的全局输出,将此输出周期性反馈给各个子滤波器以校正子滤波系统的偏差。SINS/GPS/TAN组合导航系统的仿真试验表明该算法具有更强的自适应性、滤波精度更高、鲁棒性更强。     

Code-aided adaptive equaliser for mobile communication systems

A new structure for a code-aided adaptive equaliser is proposed for mobile communication systems. The structure aims to improve the tracking capability of a receiver that combines equalisation and coding. Simulation results show that the code-aided adaptive equaliser performs particularly well over mobile channels that fade at a moderate rate. Compared to a conventional equaliser, an order of magnitude reduction in bit error rate is achieved     

Adaptive fuzzy multilevel median filter

A modified multilevel median filter (MLMF) incorporating the fuzzy associative memory (FAM) system is proposed in this correspondence. The modified method-the adaptive fuzzy multilevel median filter (AFMMF)-overcomes some disadvantages common to most of the conventional MLMF. Experimental results demonstrated that the performance of the AFMMF is superior to that of conventional MLMF in dealing with "short-line-like" noise while preserving edges.     

Image sequence stabilisation using fuzzy adaptive Kalman filtering

Image sequence stabilisation based on fuzzy adaptive Kalman filtering of absolute frame displacements is proposed. Two Kalman filters are operated in parallel, one of which is used as a reference filter and is run with a constant high process noise variance to enable smooth and close tracking of global camera displacements. The process noise variance of the stabilisation filter is adaptively varied according to the residual between the stabilisation filter and the reference filter output.     

Real-time separation of discontinuous adventitious sounds fromvesicular sounds using a fuzzy rule-based filter

The separation of pathological discontinuous adventitious sounds (DAS) from vesicular sounds (VS) is of great importance to the analysis of lung sounds since DAS are related to certain pulmonary pathologies. An automated way of revealing the diagnostic character of DAS, by isolating them from VS, based on their nonstationarity, is presented. The proposed algorithm uses two adaptive network-based fuzzy inference systems to compose a generalized fuzzy rule-based stationary-nonstationary filter (GFST-NST). The training procedure of the fuzzy inference systems involves the outputs of the wavelet transform-based stationary-nonstationary filter (WTST-NST), proposed by Hadjileontiadis and Panas (1997). The basic idea of the GFST-NST was initially proposed by the authors with the introduction of the fuzzy rule-based stationary-nonstationary filter (FST-NST) (1997), tested with the separation of crackles from VS. The main contribution of this paper is the modification of the structure of the FST-NST filter to a serial-type fuzzy filter that, unlike the parallel operation of the FST-NST filter, sends a predicted stationary signal (VS) into the predictor of the nonstationary (DAS). Applying the GFST-NST filter to fine-coarse crackles and squawks, selected from three lung sound databases, the coherent structure of DAS is revealed and they are separated from VS. The separation performance of the GFST-NST filter was evaluated through quantitative and qualitative indexes that proved its efficiency and superiority against the FST-NST filter. When compared to the WTST-NST filter, the GFST-NST filter performed similarly in accuracy and objectiveness, but in a faster way. Thus, the GFST-NST filter combines the separation accuracy of the WTST-NST filter with the real-time implementation of the FST-NST filter, so it can easily be used in clinical medicine as a module of an integrated intelligent patient evaluation system     

机载航电系统中多源信息模糊自适应融合技术

为了保障导航的精度与可靠性,目前常采用多源信息融合导航。针对ADS/IRS/GPS组合导航系统,采用基于自适应信息分配的联邦滤波结构处理信息融合问题,并把模糊推理技术融入到ADS/IRS卡尔曼滤波器中,对IRS/GPS子滤波器采用紧组合模式,上述结构算法能对多源导航信息进行最优融合与处理。建立了ADS/IRS模糊自适应卡尔曼滤波模型以及IRS/GPS紧组合滤波模型,设计了自适应信息分配的联邦滤波算法,并进行了仿真,仿真结果验证了设计算法的有效性。     

Adaptive active noise equaliser

The authors propose an adaptive active noise equaliser (AANE) with improved performance over a conventional active noise equalisation (ANE) system. The novel AANE system can adaptively equalise the residual noise power into a desired range when the primary noise power changes drastically. Computer simulations support the proposed algorithm