An infinite impulse response lattice filter for adaptive line enhancement

The least-squares lattice filter is used to implement an infinite-impulse-response adaptive filter for the enhancement of narrowband signals in the presence of white or finitely correlated noise. The advantages of infinite impulse response filters for adaptive line enhancement are discussed. The performance of the proposed technique is illustrated by simulation results.     

A pipelined adaptive lattice filter architecture

The stochastic gradient adaptive lattice filter is pipelined by the application of relaxed look-ahead. This form of look-ahead maintains the functional behavior of the algorithm instead of the input-output mapping and is suitable for pipelining adaptive filters. The sum and product relaxations are employed to pipeline the filter. The hardware complexity of the pipelined filters is the same as for the sequential filter and is independent of the level of pipelining or speedup. Two pipelined architectures along with their convergence analyses are presented to illustrate the tradeoff offered by relaxed look-ahead. Simulation results supporting the conclusions of the convergence analysis are provided. The proposed architectures are then employed to develop a pipelined adaptive differential pulse-code modulation (DPCM) codec for video compression applications. Speedup factors up to 20 are demonstrated via simulations with image data     

一种基于格型滤波的二阶Volterra自适应均衡算法

针对随着Volterra滤波器记忆元增多,计算复杂度成指数快速增加的问题,本文提出了一种基于格型滤波的二阶Volterra自适应算法.利用格型滤波器正交化处理输入信号,实现了二次项信号解耦,从而减少了自适应算法的输入信号自相关矩阵条件数,提高了自适应算法性能;同时也实现了二次项的权系数矩阵对角化,大大减少了二次项的权系数,使得滤波器权系数与输出成线性关系,权系数的LMS算法变得更加简便.计算机仿真结果表明,本文所提出的算法无论对线性信道还是非线性信道都有比文献[5]算法更快的收敛速度和更好的稳态性能.     

一种基于格型正交化的二阶Volterra自适应滤波算法

针对 Volterra 自适应滤波器输入信号相关性或附加的非线性畸变的增强使自适应滤波器性能下降的问题,本文提出基于格型正交化的二阶 Volterra 自适应滤波算法.先对输入信号进行格型预处理,得到互相正交的后向预测误差信号;然后将其作为自适应滤波器的输入,从而大大降低了一次项、平方项和交叉乘积项信号各项之间的耦合,改善了自适应算法的收敛性能.有源噪声对消的仿真结果表明,在输入噪声强相关和附加较强非线性畸变时本算法仍具有较好的消噪性能.     

基于FPGA的梯度自适应格型滤波器设计

对于高灵敏度的数字信号的处理需要使用数值特性优良的格型滤波器。利用EDA技术设计了梯度自适应格型滤波器。实验表明更新反射系数的步长应随着模块数的增加逐步减小。对梯度自适应格型滤波器的单独模块采用驰豫超前技术设计,显著提高了FPGA的运行时钟速率。     

Inherent matrix identities on ARMA lattice filter realizationalgorithm and their application

Presents the matrix identities that are inherent in the solution of the normal equations for an ARMA lattice filter. This derivation also makes clear the relationship between the recursive least squares (RLS) method and the ARMA lattice filter realization algorithm. Further, as an application of the matrix identities, a new method for model identification with frequency weighting (MIFW) is presented     

An adaptive resonant filter

A solid-state adaptive (analog storage) device with stable electrical characteristics is described and demonstrated. The device is a resonant bandpass electronic filter with adaptable voltage gain; that is, the voltage gain-frequency transfer characteristic can be "set" to different values of attenuation by the application of an adapt signal and will retain that "setting" after the adapt signal has been removed. Ferroelectric materials are used as the dielectric in a filter structure composed of two capacitors bonded together so that resonant mechanical vibrations established in one (the input resonator) are coupled to the other (the output resonator). Converse and direct piezoelectric effects generate the mechanical vibrations and the output voltages, respectively. Ferroelectric effects in either capacitor provide the analog storage capabilities. The acoustical coupling mechanism employed in the device design results in electrically stable device characteristics. Previous ferroelectric adaptive devices used unstable field effect coupling mechanisms which led to unacceptable device performance. Experimental adaptive resonant filters fabricated with ceramic lead zirconate-lead titanate material compositions are discussed. These filters have electronic Q values near 100 at resonant frequencies in the range 10²to 10⁷Hz. The voltage gain-frequency characteristic has a maximum value at resonance of about 0 to +10 dB. Application of a voltage adapt pulse (100 to 300 volts) of low energy (mJ) to either side of the filter can adapt the entire gain characteristic by any value between 0 and about -60 dB within an arbitrary switching time (limited to a practical range of roughly 10⁺³to 10^-4seconds) as determined by the pulse amplitude. Voltage gain settings are electrically stable and can be reproduced by the same or an equivalent sequence of adapting pulses.     

基于随机加权估计的Sage自适应滤波及其在导航中的应用

为了克服Kalman滤波和Sage自适应滤波的缺点,在分析基于新息向量、残差向量和状态改正数向量的自适应协方差估计存在问题的基础上,提出根据新息向量、残差向量和状态改正数对滤波精度影响的不同程度,采用随机加权法对新息向量、残差向量和状态改正数进行估计,以得到观测噪声协方差矩阵和系统动态噪声协方差矩阵.进一步,利用随机加权法对观测噪声协方差阵和系统噪声协方差阵进行估计,以提高动态导航定位的滤波解算精度.研究结果表明,基于随机加权估计的Sage自适应滤波效果明显优于基于算术平均值估计的滤波方法.     

Analysis of the frequency domain adaptive filter

The purpose of this note is to demonstrate significant analytical simplifications for studying the behavior of adaptive filtering in the frequency domain as opposed to studying the behavior of adaptive filtering in the time domain. A closed form expression, for the single complex weight in the frequency domain adaptive filter, is presented which allows significant statistical analysis to be performed. The mean-square error of the filter is evaluated as a function of the algorithm step size and the signal and noise powers.     

An adaptive morphological filter for image processing

Novel types of opening operator (NOP) and closing operator (NCP) are proposed. An adaptive morphological filter is then constructed on the basis of the NOP and NCP. The filter can remove any details consisting of fewer pixels than a given number N, while preserving the other details. Efficient algorithms are also developed for the implementation of the NOP and NCP.     

Fast-converging minimum frequency error RLS lattice filter for narrowband interference with discrete frequency steps

This paper discusses the fundamental convergence and frequency tracking properties of the recursive-least-squares (RLS) lattice filter in the presence of narrowband interference (NBI) whose frequency varies in discrete steps. It is shown for filters of this type, that the residual forward energy (RFE) after a frequency transition is a function of the input signal-to-noise ratio (SNR), separation of the sequential frequencies and the filter time constant and is exponentially decaying in nature. Reducing the RFE is important in removing unwanted transient artefacts from the desired signal. The convergence behaviour of the RLS algorithm based on a posteriori estimation errors is analysed under a number of conditions by varying the SNR and frequency step size. In order to limit the impact of the RFE while maintaining a minimum frequency tracking error in steady conditions, a fast-converging minimum frequency error (FCMFE) RLS lattice filter is suggested. For comparison, a least-mean-square (LMS) based gradient-adaptive lattice (GAL) filter is also analysed for this class of narrowband interference.     

An adaptive recursive LMS filter

An adaptive, recursive, least mean-square-digital filter is heuristically derived that has the computational simplicity of existing transversal adaptive filters, with the additional capability of producing poles in the filter transfer function. Simulation results are presented to demonstrate its capability.     

Improved Cramer-Rao lower bounds for phase and frequency estimationwith M-PSK signals

We derive new Cramer-Rao lower bounds (CRBs) for the estimation of carrier phase and frequency offset from an unmodulated carrier or from a M-PSK data signal. The new CRBs are obtained formally from the exact likelihood function for the carrier phase and frequency offset, build from a block of received phase samples, and are applicable for a general alphabet size M. The bounds are compared with other previously obtained bounds (which also take into account the effect of random phase modulation) and with the performance of some popular feedforward algorithms for carrier phase and frequency offset estimation     

An adaptive Kalman filter for ECG signal enhancement

The ongoing trend of ECG monitoring techniques to become more ambulatory and less obtrusive generally comes at the expense of decreased signal quality. To enhance this quality, consecutive ECG complexes can be averaged triggered on the heartbeat, exploiting the quasi-periodicity of the ECG. However, this averaging constitutes a tradeoff between improvement of the SNR and loss of clinically relevant physiological signal dynamics. Using a bayesian framework, in this paper, a sequential averaging filter is developed that, in essence, adaptively varies the number of complexes included in the averaging based on the characteristics of the ECG signal. The filter has the form of an adaptive Kalman filter. The adaptive estimation of the process and measurement noise covariances is performed by maximizing the bayesian evidence function of the sequential ECG estimation and by exploiting the spatial correlation between several simultaneously recorded ECG signals, respectively. The noise covariance estimates thus obtained render the filter capable of ascribing more weight to newly arriving data when these data contain morphological variability, and of reducing this weight in cases of no morphological variability. The filter is evaluated by applying it to a variety of ECG signals. To gauge the relevance of the adaptive noise-covariance estimation, the performance of the filter is compared to that of a Kalman filter with fixed, (a posteriori) optimized noise covariance. This comparison demonstrates that, without using a priori knowledge on signal characteristics, the filter with adaptive noise estimation performs similar to the filter with optimized fixed noise covariance, favoring the adaptive filter in cases where no a priori information is available or where signal characteristics are expected to fluctuate.     

An adaptive filter for smoothing noisy radar images

Radar images are corrupted by multiplicative noise due to fading. This paper presents an algorithm for smoothing noisy radar images. The algorithm is easily implemented in the spatial domain and is computationally very efficient. By adapting the filter parameters to local statistics, it is shown that the filter preserves edges.     

An adaptive order-statistic noise filter for gamma-corrected imagesequences

Original video signals are often corrupted by a certain amount of noise originating from the camera electronics. As a result of the gamma correction in cameras, the observed noise is signal dependent. We present a spatio-temporal order-statistic (OS) noise filter that takes into account the gamma correction in the camera. The calculation of the filter coefficients requires higher-order order-statistics (HOOS) of the noise process. We make use of a range test (RT) to determine locally from which neighboring signal values an estimate should be formed. The noise filter that we arrive at is adaptive and computationally efficient.     

Convergence analysis of the adaptive lattice filter for a mixed Gaussian input sequence

The convergence performance of the adaptive lattice filter (ALF) using the stochastic gradient algorithm is measured by the convergence speed and estimated error variance of the PARCOR coefficient. The convergence properties of the ALF are analysed when the filter input has a Gaussian mixture distribution. First, theoretical expressions for the convergence rate and asymptotic error variance of the PARCOR coefficient are derived, and then the theoretical expressions are compared for single and mixed Gaussian input sequences. It is shown that the convergence performance of the ALF improves as the distribution of the input signal approaches a single Gaussian distribution.     

An efficient lattice predictor algorithm for instantaneous frequency estimation

An efficient method for spectral analysis of non-stationary signals is proposed. The signals are modelled as time-varying autoregressive (AR) processes and the relevant AR parameters are obtained from the adaptive lattice predictor coefficients minimizing the forward/backward prediction errors. In this paper it is proposed to use the sign algorithm, which computes the pertinent coefficients using only the signs of the forward/backward prediction errors at each stage. This method requires less number of multiplications than other adaptive lattice predictor algorithms. The performance of this method is compared with that of the adaptive lattice predictor using the least mean square algorithm for the problems of estimating instantaneous frequencies of FM signals via computer simulations.     

An adaptive temporal-spatial filter for MPEG decoded video signals

A new adaptive post-processing algorithm for the MPEG decoded video sequences is proposed. We use a motion compensated averaging filter to reduce the noises in the temporal domain and an adaptive spatial filter to remove noise in the spatial domain and preserve the edge of different orientations in the image. A MPEG decoded video sequence called table tennis is processed by our proposed filter. The post-processed video sequence shows that its image quality is improved, especially of the moving objects.     

An adaptive speckle suppression filter for medical ultrasonic imaging

An adaptive smoothing technique for speckle suppression in medical B-scan ultrasonic imaging is presented. The technique is based on filtering with appropriately shaped and sized local kernels. For each image pixel, a filtering kernel, which fits to the local homogeneous region containing the processed pixel, is obtained through a local statistics based region growing technique. The performance of the proposed filter has been tested on the phantom and tissue images. The results show that the filter effectively reduces the speckle while preserving the resolvable details. The simulation results are presented in a comparative way with two existing speckle suppression methods.