Initial and boundary conditions in multidimensional wave digital filter algorithms for plate vibration

Recently, multidimensional wave digital filter (MDWDF) structures have been proposed for the modeling of plate vibration problems. In this paper, we discuss how initial and boundary conditions may be properly embedded into such an algorithm in terms of the state quantities that are an integral part of the algorithm. Due to the essential feature of fully-local interconnectivity in the MDWDF model, different types of boundary conditions can be easily satisfied in a very simple and efficient manner. Instead of remodifying the whole algorithm, usually required by finite elements based methods, boundary conditions in terms of state outputs are simply attached to the model. This feature is especially useful when dealing with the mixed-edges boundary conditions frequently encountered in practice. Graphical results obtained from implementing the MDWDF algorithm are given to further demonstrate the capacities of the method in efficiently handling a fourth-order Mindlin plate vibration system with various types of boundary conditions.     

Quasi-periodic spatiotemporal filtering.

This paper presents the online estimation of temporal frequency to simultaneously detect and identify the quasiperiodic motion of an object. We introduce color to increase discriminative power of a reoccurring object and to provide robustness to appearance changes due to illumination changes. Spatial contextual information is incorporated by considering the object motion at different scales. We combined spatiospectral Gaussian filters and a temporal reparameterized Gabor filter to construct the online temporal frequency filter. We demonstrate the online filter to respond faster and decay faster than offline Gabor filters. Further, we show the online filter to be more selective to the tuned frequency than Gabor filters. We contribute to temporal frequency analysis in that we both identify ("what") and detect ("when") the frequency. In color video, we demonstrate the filter to detect and identify the periodicity of natural motion. The velocity of moving gratings is determined in a real world example. We consider periodic and quasiperiodic motion of both stationary and nonstationary objects.     

Noise reduction of image sequences using motion compensation andsignal decomposition

In this paper, a new spatio-temporal filtering method for removing noise from image sequences is proposed. This method combines the use of motion compensation and signal decomposition to account for the effects of object motion. Because of object motion, image sequences are temporally nonstationary, which requires the use of adaptive filters. By motion compensating the sequence prior to filtering, nonstationarities, i.e., parts of the signal that are momentarily not stationary, can be reduced significantly. However, since not all nonstationarities can be accounted for by motion, a motion-compensated signal still contains nonstationarities. An adaptive algorithm based on order statistics is described that decomposes the motion-compensated signal into a noise-free nonstationary part and a noisy stationary part. An RLS filter is then used to filter the noise from the stationary signal. Our new method is experimentally compared with various noise filtering approaches from literature.     

Relationship between Kalman and notch filters used in dynamic ship positioning systems

In dynamic ship positioning systems notch filters have been used mainly to remove the unwanted wave motion signals. Recently, Kalman filters have been introduced for this purpose. It is demonstrated that for this application the stationary Kalman filter is approximated by a notch filter together with a low-pass filter in cascade.     

基于H∞滤波器的红外小目标运动预测和跟踪方法

根据H∞滤波理论,提出了基于H∞滤波预测技术的红外图像小目标运动预测和跟踪方法,为了降低模型阶数以加快图像处理速度,滤波过程被分解在水平和垂直两个方向上分别进行,即将滤波器分解为x、y方向上两个子滤波器．H∞滤波器是一种基于最优化最坏情况下的滤波技术,它对噪声源的要求不高,能较好地应用在复杂场景下的目标运动预测与跟踪．实验证实了在噪声源不能确定或是未知的情况下,它比Kalman滤波器对红外小目标的运动预测更加准确并具有更好抗扰动性．     

广义切比雪夫型LC滤波器的设计*

提出一种广义切比雪夫型LC滤波器的设计方法,带外传输零点可以是任意设定,其带外特性既可以对称,也可以不对称.采用此方法设计出的LC滤波器,其带内波动可以与最大平坦型滤波器一样很小,而矩形系数可以与椭圆函数型滤波器一样好.每一个传输零点的位置可以由一个元器件的取值大小控制.与椭圆函数型LC滤波器相比,相同数量的元器件,它可以实现更陡的截止特性.     

An Applied Method for Designing Maximally Decimating Non-uniform Filter Banks

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Non-separable extensions of quadrature mirror filters to multipledimensions

Generalized non-separable extensions of quadrature mirror filter (QMF) banks to two and three dimensions, in which the orientation specificity of the high-pass filters is greatly improved, are described. In particular, extensions to two dimensions with hexagonal symmetry, and 3-D spatiotemporal extensions with rhombic-dodecahedral symmetry, are discussed. Although these filters are conceived and designed on nonstandard sampling lattices, they can be applied to rectangularly sampled images. As in one dimension, these transformations can be hierarchically cascaded to form a multiscale pyramid representation. A set of example filters is designed and applied to the problems of image compression, progressive transmission, orientation analysis, and motion analysis     

基于自适应卡尔曼滤波的机动目标跟踪算法

针对一般卡尔曼滤波融合跟踪方法无法实现对机动目标的有效跟踪问题,提出一种自适应卡尔曼滤波融合方法,设计一种能够提供目标开始机动瞬时估计的目标机动探测器,反复对目标的加速机动进行估计,当确定目标开始机动时,卡尔曼滤波模型将自适应地调整为目标机动状态模型。最后,通过仿真实验对比分析,证明文中所提方法优于一般卡尔曼滤波融合方法。     

Optimal temporal interpolation filter for motion-compensated frame rate up conversion.

Frame rate up conversion (FRUC) methods that employ motion have been proven to provide better image quality compared to nonmotion-based methods. While motion-based methods improve the quality of interpolation, artifacts are introduced in the presence of incorrect motion vectors. In this paper, we study the design problem of optimal temporal interpolation filter for motion-compensated FRUC (MC-FRUC). The optimal filter is obtained by minimizing the prediction error variance between the original frame and the interpolated frame. In FRUC applications, the original frame that is skipped is not available at the decoder, so models for the power spectral density of the original signal and prediction error are used to formulate the problem. The closed-form solution for the filter is obtained by Lagrange multipliers and statistical motion vector error modeling. The effect of motion vector errors on resulting optimal filters and prediction error is analyzed. The performance of the optimal filter is compared to nonadaptive temporal averaging filters by using two different motion vector reliability measures. The results confirm that to improve the quality of temporal interpolation in MC, the interpolation filter should be designed based on the reliability of motion vectors and the statistics of the MC prediction error.     

Numerical Stability Verification of a Two-Dimensional Time-Dependent Nonlinear Shallow Water System Using Multidimensional Wave Digital Filtering Network

This paper aims to study the stability effects of a two-dimensional time-dependent nonlinear shallow water (NLSW) system based on the concordance analysis of necessary and sufficient conditions derived from a multidimensional wave digital filtering (MDWDF) network. Approximating the differential equations used to describe elements of a MD passive electrical circuit by grid-based difference equations, the satisfactory Courant–Friedrichs–Levy condition usually known to be necessary are derived with various initial conditions to provide theoretical support for the existence of a MD passive dynamical system and thus stability of the discrete equivalent. Together with the evaluation of the system’s energy and hence solution error propagation that both arise directly and sufficiently to the stability of MDWDF networks, the numerical convergence of the network can be fully established. As a consequence, all instability related aspects in relation to computational errors and overflow corrections are fully excluded leading to uniquely a high degree of robustness of MDWDF architecture. Feasible comparisons are made with a finite element method implemented in the COMSOL Multiphysics to confirm the verification process.     

METEOR: a constraint-based FIR filter design program

It is proposed to specify a filter only in terms of upper and lower limits on the response, find the shortest filter length which allows these constraints to be met, and then find a filter of that order which is farthest from the upper and lower constraint boundaries in a minimax sense. The simplex algorithm for linear programming is used to find a best linear-phase FIR filter of minimum length, as well as to find the minimum feasible length itself. The simplex algorithm, while much slower than exchange algorithms, also allows the incorporation of more general kinds of constraints, such as concavity constraints (which can be used to achieve very flat magnitude characteristics). Examples are given to illustrate how the proposed and common approaches differ, and how the proposed approach can be used to design filters with flat passbands, filters which meet point constraints, minimum phase filters, and bandpass filters with controlled transition band behavior     

Theory and design of two-parallelogram filter banks

It is well known that the analysis and synthesis filters of orthonormal DFT filter banks can not have good frequency selectivity. The reason for this is that each of the analysis and synthesis filters have only one passband. Such frequency stacking (or configuration) in general does not allow alias cancellation when the individual filters have good stopband attenuation. A frequency stacking of this nature is called nonpermissible and should be avoided if good filters are desired. In a usual M-channel filter bank with real-coefficient filters, the analysis and synthesis filters have two passbands. It can be shown that the configuration is permissible in this case. Many designs proposed in the past demonstrate that filter banks with such configurations can have perfect reconstruction and be good filters at the same time. We develop the two-parallelogram filter banks, which is the class of 2-D filter banks in which the supports of the analysis and synthesis filters consist of two parallelograms. The two-parallelogram filter banks are analyzed from a pictorial viewpoint by exploiting the concept of permissibility. Based on this analysis, we construct and design a special type of two-parallelogram filter banks, namely, cosine-modulated filter banks (CMFB). In two-parallelogram CMFB, the analysis and synthesis filters are cosine-modulated versions of a prototype that has a parallelogram support. Necessary and sufficient conditions for perfect reconstruction of two-parallelogram CMFB are derived     

Power Reduction in Custom CMOS Digital Filter Structures

Today the main optimization parameter of digital filters is the filter order. By the aid of two implemented filters we will show that both power and speed can be enhanced if the optimization effort is made on reducing the filter coefficient lengths rather than minimizing the order. Both filters have been designed from the same specification, one as a standard minimum order filter, the other as a filter with short coefficients found by a computer search. The minimum order filter is of order three with seven bits long coefficients. The coefficient optimized filter is of order six with two bits long coefficients. Both filters were implemented with bit-serial fixed coefficient arithmetic in two's complement representation in a 0.8µ, two metal layers CMOS process. Measurements show an eightfold speedup at half the power consumption and only 30% area cost for the coefficient optimized filter.     

Permutation weighted order statistic filter lattices

We introduce and analyze a new class of nonlinear filters called permutation weighted order statistic (PWOS) filters. These filters extend the concept of weighted order statistic (WOS) filters, in which filter weights associated with the input samples are used to replicate the corresponding samples, and an order statistic is chosen as the filter output. PWOS filters replicate each input sample according to weights determined by the temporal-order and rank-order of samples within a window. Hence, PWOS filters are in essence time-varying WOS filters. By varying the amount of temporal-rank order information used in selecting the output for a given observation window size, we obtain a wide range of filters that are shown to comprise a complete lattice structure. At the simplest level in the lattice, PWOS filters reduce to the well-known WOS filter, but for higher levels in the lattice, the obtained selection filters can model complex nonlinear systems and signal distortions. It is shown that PWOS filters are realizable by a N! piecewise linear threshold logic gate where the coefficients within each partition can be easily optimized using stack filter theory. Simulations are included to show the advantages of PWOS filters for the processing of image and video signals.     

Analysis of the properties of median and weighted median filtersusing threshold logic and stack filter representation

The deterministic properties of weighted median (WM) filters are analyzed. Threshold decomposition and the stacking property together establish a unique relationship between integer and binary domain filtering. The authors present a method to find the weighted median filter which is equivalent to a stack filter defined by a positive Boolean function. Because the cascade of WM filters can always be expressed as a single stack filter this allows expression of the cascade of WM filters as a single WM filter. A direct application is the computation of the output distribution of a cascade of WM filters. The same method is used to find a nonrecursive expansion of a recursive WM filter. As applications of theoretical results, several interesting deterministic and statistical properties of WM filters are derived     

Adaptive Linear Predictive Coding of Time-Varying Images Using Multidimensional Recursive Least Squares Ladder Filters

This paper presents several adaptive linear predictive coding techniques based upon extension of recursive ladder filters to two and three dimensions (2-D/3-D). A 2-D quarter-plane autoregressive ladder filter is developed using a least square criterion in an exact recursive fashion. The 2-D recursive ladder filter is extended to a 3-D case which can adaptively track the variation of both spatial and temporal changes of moving images. Using the 2-D/3-D ladder filters and a previous frame predictor, two types of adaptive predictor-control schemes are proposed in which the prediction error at each pel can be obtained at or close to a minimum level. We also investigate several modifications of the basic encoding methods. Performance of the 2D/3-D ladder filters, their adaptive control schemes, and variations in coding methods are evaluated by computer simulations on two real sequences and compared to the results of motion compensation and frame differential coders. As a validity test of the ladder filters developed, the error signals for the different predictors are compared and the visual quality of output images is verified.     

A Fractionally Delaying Complex Hilbert Transform Filter

In this paper, we present a novel complex discrete-time filter. This is a fractionally delaying (FD) Hilbert transform filter (HTF) further called the FD HTF. The filter is based on a pair of rotated variable fractional delay (VFD) filters. It is capable of performing the Hilbertian as well as VFD filtering of the incoming discrete-time signal at the same time. Thus, one can substitute a cascade of the HTF and the VFD filters with an aggregated filter proposed here. The technique is simple to implement. The advantages lie in lower total delay introduced by the compound filter and in a modular structure. The rotated VFD filters in the pair differ only in the value of one parameter - the VFD. The proposed FD HTF can be applied to adaptive quadrature sub-sample estimation of delay.     

Radio imaging of moving targets: the one-dimensional case(microwave range)

The detection of moving targets by passive radio temperature measurements is studied. A radio image is reconstructed by linear spatial filtering of simultaneous measured brightness samples, obtained by multiple regularly spaced antenna beams. With fixed spatial filters, the receiver integration time must be short enough to freeze motion, thus limiting the signal-to-noise ratio obtained in the reconstruction image. It is shown that in the one-dimensional case a time-varying matched spatial filter yields the same signal-to-noise ratio in the reconstructed image as would be obtained from a stationary target with a fixed matched filter     

Approximation of complex IIR bandpass filters without arithmetic symmetry

Complex transfer functions are not restricted to having complex-conjugate symmetry in the frequency-domain, as is the case for real filters. This gives them more flexibility when they are used in communication systems with complex signals, such as intermediate frequency signals of wireless communication systems. This paper describes a set of algorithms and procedures that can be used in solving the approximation problem involved in deriving complex infinite-impulse-response bandpass transfer functions directly, without the requirement of first designing a real-transfer-function prototype filter, which is then frequency translated. Because the requirement for a real prototype filter is eliminated, the filters need not have arithmetic symmetry; this results in superior stopbands with smaller filter orders. The procedures can be used for both continuous and discrete-time filters, can allow for arbitrary stopband specifications, and can be used for either equi-ripple or monotonic passbands.