Iterative reweighted least-squares design of FIR filters

Develops a new iterative reweighted least squares algorithm for the design of optimal L_p approximation FIR filters. The algorithm combines a variable p technique with a Newton's method to give excellent robust initial convergence and quadratic final convergence. Details of the convergence properties when applied to the L_p optimization problem are given. The primary purpose of L_p approximation for filter design is to allow design with different error criteria in pass and stopband and to design constrained L₂ approximation filters. The new method can also be applied to the complex Chebyshev approximation problem and to the design of 2D FIR filters     

Filter design for MIMO sampling and reconstruction

We address the problem of finite impulse response (FIR) filter design for uniform multiple-input multiple-output (MIMO) sampling. This scheme encompasses Papoulis' generalized sampling and several nonuniform sampling schemes as special cases. The input signals are modeled as either continuous-time or discrete-time multiband input signals, with different band structures. We present conditions on the channel and the sampling rate that allow perfect inversion of the channel. Additionally, we provide a stronger set of conditions under which the reconstruction filters can be chosen to have frequency responses that are continuous. We also provide conditions for the existence of FIR perfect reconstruction filters, and when such do not exist, we address the optimal approximation of the ideal filters using FIR filters and a minmax l/sub 2/ end-to-end distortion criterion. The design problem is then reduced to a standard semi-infinite linear program. An example design of FIR reconstruction filters is given.     

Designs of Chebyshev-type complex FIR filters and digitalbeamformers with linear-phase characteristics

Based on the theory of optimal polynomial approximation, the authors present a complex alternation theorem which shows the existence of Chebyshev complex FIR filters. According to the theorem, a method for designing Chebyshev-type complex FIR filter and DBFs with linear-phase characteristics is proposed. A zero exchange algorithm and the related procedures are used to iteratively find the best approximation to a variety of desired frequency responses and directivity patterns. Several examples are included to show the efficacy of the designs of FIR filters with multistop-/multipassband responses, DBFs with pencil beams and local low sidelobes, and pattern synthesis with a shaped mainlobe     

Design of 2-D FIR Filters by a Feedback Neural Network

A Hopfield-type neural network for the design of 2-D FIR filters is proposed. The network is contrived to have an energy function that coincides with the sum-squared error of the approximation problem at hand and by ensuring that the energy is a monotonic decreasing function of time, the approximation problem can be solved. Two solutions are obtained. In the first the 2-D FIR filter is designed on the basis of a specified amplitude response and in the second a filter that has specified maximum passband and stopband errors is designed. The network has been simulated with HSPICE and design examples are included to show that this is an efficient way of solving the approximation problem for 2-D FIR filters. The neural network has high potential for implementation in analog VLSI and can, as a consequence, be used in real-time applications.     

可规划相位FIR滤波器的神经网络设计方法

本文针对可规划相频响应的实系数FIR滤波器的逼近问题,采用一个三层复激活函数前馈神经网络来实现。该网络隐层各神经元的激活函数为复指数函数,将滤波器系数作为隐层各神经元到输出层的连接权值,通过对误差函数的最小化来调整权值,并根据网络特性与所要设计的滤波器的特点,提出了一些实际设计中训练样本集选取与误差加权值设置的规则。依托所采用的神经网络,根据上述规则,进行了两例可规划相频特性的实系数FIR滤波器的设计,结果表明所设计滤波器的相频响应较好地满足了设计要求。     

Minimax design of two-channel low-delay perfect-reconstruction FIRfilter banks

The authors deal with the design problem of low-delay perfect-reconstruction filter banks for which the FIR analysis and synthesis filters have equiripple magnitude response. Based on the minimax error criterion, the design problem is formulated in such a manner that the coefficients for the FIR analysis filters can be found by minimising the weighted peak error of the designed analysis filters, subject to the perfect-reconstruction constraints. A design technique based on a modified dual-affine scaling variant of Karmarkar's (1989) algorithm, in conjunction with approximation schemes, is then developed for solving the resulting nonlinear optimisation problem. The effectiveness of the proposed design technique is demonstrated by several simulation examples     

The use of model reduction techniques for designing IIR filterswith linear phase in the passband

A technique to design IIR filters with linear phase in the passband is presented. This technique is based on model reduction of an FIR prototype using frequency weighting to improve the approximation in the transition region. Filters designed using the proposed technique are compared with linear-phase FIR designs and to IIR phase equalized designs with respect to computational complexity and group delay. It is shown that for highly selective filters, the proposed technique offers a good compromise     

An iterative algorithm for optimal design of non-frequency-selective FIR digital filters

This paper proposes a novel iterative algorithm for optimal design of non-frequency-selective Finite Impulse Response （FIR） digital filters based on the windowing method. Different from the traditional optimization concept of adjusting the window or the filter order in the windowing design of an FIR digital filter, the key idea of the algorithm is minimizing the approximation error by successively modifying the design result through an iterative procedure under the condition of a fixed window length. In the iterative procedure, the known deviation of the designed frequency response in each iteration from the ideal frequency response is used as a reference for the next iteration. Because the approximation error can be specified variably, the algorithm is applicable for the design of FIR digital filters with different technical requirements in the frequency domain. A design example is employed to illustrate the efficiency of the algorithm.     

Chebyshev Design of Linear-Phase FIR Filters With Linear Equality Constraints

By using basis transformation, the Chebyshev approximation of linear-phase finite-impulse response (FIR) filters with linear equality constraints can be converted into an unconstrained one defined on a new function space. However, since the Haar condition is not necessarily satisfied in the new function space, the alternating property does not hold for the solution to the resulted unconstrained Chebyshev approximation problem. A sufficient condition for the best approximation is obtained in this brief, and based on this condition, an efficient single exchange algorithm is derived for the Chebyshev design of linear-phase FIR filters with linear equality constraints. Simulations show that the proposed algorithm can converge to the optimal solution in most cases and to a near-optimal solution otherwise. Design examples are presented to illustrate the performance of the proposed algorithm.     

Image Decimation and Interpolation Techniques Based on Frequency Domain Analysis

A scheme for a spatial domain image data preprocessing decimation and postprocessing interpolation is presented. The scheme is implemented by appropriate FIR digital filters. Frequency and patial domain specifications are discussed in the design of the corresponding digital filters. Fast approximation techniques in the spatial domain are presented.     

Theory and Design of Linear-Phase Minimax FIR Filters with Mixed Constraints in the Frequency Domain

The alternation theorem is the core of efficient approximation algorithms for the minimax design of finite-impulse response (FIR) filters. In this paper, an extended alternation theorem with additional mixed constraints, i.e., equality-and-inequality constraints, is obtained. Then, an efficient multiple-exchange algorithm based on the extended theorem is presented for designing linear-phase FIR filters with frequency mixed constraints in the minimax sense. Further, convergence of the algorithm is established. Several design examples and comparisons with existing techniques are presented, and the simulation results show that the proposed algorithm is numerically more efficient and guaranteed to converge to the optimal solution.     

Frequency domain design of FIR and IIR Laplacian of Gaussian filters for edge detection

This work addresses the design of LoG filters in the frequency domain within a structure formed by the cascade of quasi-Gaussian and discrete Laplacian filters. The main feature of such a structure is that it requires half the number of convolutions of the classical structure in which the LoG transfer function is expressed as the sum of two separable transfer functions of 1-D Gaussian and LoG type. Such a perspective allows one to rephrase the design of IIR and FIR filters for edge detection as a frequency domain approximation problem solvable by standard digital filter design tools. The zero-phase IIR solutions have a good performance at low orders and approximation errors practically independent of the aperture parameter. The characteristics of the nearly linear-phase IIR filters solving the problem suggest the consideration of linear-phase FIR filters with zeros constrained on the unit circle. The use of such filters leads to remarkable computational savings with respect to the filters designed by impulse response sampling. The agreement between the edge values obtained by the filters designed according to the scheme proposed in this work and those obtained by standard techniques is very good.Work carried out with the financial support of the C.N.R.-Progetto Finalizzato Robotica, contract no. 91.01942.PF67.     

二维线性相位FIR滤波器设计的投影最小二乘算法

考虑二维线性相位矩形对称FIR滤波器的约束最小二乘设计问题,即在通带和阻带逼近误差不超过给定值的约束下使逼近误差平方和最小.提出一个投影最小二乘算法,它是一个交替地更新有效约束集及将二次误差无约束极小点(最小二乘解)逐次投影到有效约束边界的迭代过程.通过二维FIR低通圆形滤波器和方形滤波器的设计例子,对算法的性能进行了仿真,并与基于内点算法和有效集方法的设计程序进行了比较,结果表明本文算法具有很高的效率.     

Design of FIR digital filters with prescribed flatness and peak error constraints using second-order cone programming

This paper studies the design of digital finite impulse response (FIR) filters with prescribed flatness and peak design error constraints using second-order cone programming (SOCP). SOCP is a powerful convex optimization method, where linear and convex quadratic inequality constraints can readily be incorporated. It is utilized in this study for the optimal minimax and least squares design of linear-phase and low-delay (LD) FIR filters with prescribed magnitude flatness and peak design error. The proposed approach offers more flexibility than traditional maximally-flat approach for the tradeoff between the approximation error and the degree of design freedom. Using these results, new LD specialized filters such as digital differentiators, Hilbert Transformers, Mth band filters and variable digital filters with prescribed magnitude flatness constraints can also be derived.     

基于FPGA的FIR滤波器设计

数字滤波器在数字信号处理中占有很重要的地位,该文介绍了FIR滤波器的两种实现算法：乘累加算法和优化的分布式算法,其中分布式算法作为优化算法进行研究。其次,根据FIR滤波器理论,采用线性相位结构优化滤波器的设计。并给出了FIR滤波器的模块划分和FIR滤波器的主要模块的实现,最后对FIR滤波器进行了系统仿真和验证。     

On Low-Delay Frequency-Response Masking FIR Filters

This paper offers two main contributions to the theory of low-delay frequency-response masking (FRM) finite impulse response (FIR) filters. First, a thorough investigation of the low-delay FRM FIR filters and their subfilters or three different structures, referred to as narrow-, wide-, and middle-band filter structures, is given. The investigation includes discussions on delay distribution over the subfilters as well as estimation of the optimal periodicity of the periodic model filter. Second, systematic design procedures are given, with explicit formulas for distribution of the ripples and the delay to the subfilters. For each of the three structures, two design procedures are given that include joint optimization of the subfilters. The first proposal uses partly linear-phase FIR subfilters and partly low-delay FIR subfilters. Thus, it has a lower arithmetic complexity compared to the second proposal, which has exclusively low-delay FIR subfilters. The second proposal is instead more flexible and can handle a broader range of specifications. The design procedures result in low-delay FIR filters with a lower arithmetic complexity compared to previous results, for specifications with low delay and narrow transition band.     

A technique for multiple criterion approximation of FIR filters inmagnitude and group delay

In spite of the attention received by nonlinear phase (NLP) FIR filter design, the “best” way to solve this problem is still open to debate. The formulation of nonlinear phase FIR filter design in terms of simultaneous magnitude and group-delay approximation addresses the two parameters of ultimate interest for applications. The simultaneous minimization of these two functions (one of which, the group delay, rational) is approached on the basis of an original extension of the differential correction algorithm. The proposed design tool enjoys interesting theoretical properties and works very effectively. The filters obtained according to the multiple criterion optimization (MCO). Formulation are compared against filters that are optimal in the complex Chebychev norm. Then, the flexibility characteristic of MCO formulations of trading off between magnitude and group-delay performance is exemplified     

Quasi-equiripple approximation of minimum phase FIR filters by updating desired response

The authors present a numerical method for the Chebyshev approximation of minimum phase FIR digital filters. This method is based on solving a least squares (LS) problem iteratively. At each iteration, the desired response is transformed so as to have an equiripple magnitude error. This method makes it possible to design minimum phase FIR filters whose magnitude error is quasi-equiripple. Using this method, a quasi-equiripple solution is obtained very quickly. Since the proposed methods do not require any time-consuming optimisation procedure, they require less computational complexity than conventional methods. Finally, some examples to illustrate the advantage of the proposed methods are shown.     

Comments on "FIR digital filter design techniques using weighted Chebyshev approximation"

The history of the FIR filter approximation problem, as recently presented by Rabiner, McClellan, and Parks, is deficient in some areas and misleading in others. Some corrections are suggested. In addition to a brief discussion of different approaches to the design of FIR digital filters, areas into which present methods can be readily extended are outlined. The relationship between the parks and McClellan method and the upper and lower function method is presented.     

Weighted least-squares approximation of FIR by IIR digital filters

This paper presents a method for the weighted least-squares approximation of finite impulse response (FIR) filters by infinite impulse response (IIR) filters. It is shown, how a solution to this approximation problem can be obtained by solving a related pure least-squares approximation problem. For the latter, we utilize a generalized version of a previously published technique with low computational complexity and guaranteed stability of the IIR filters. Unlike the well-established model-reduction approaches that are carried out in the state space, our method works directly with the numerator and denominator coefficients of the transfer functions. Thus, the influence of finite-precision arithmetic on the results is small. This makes our approach applicable for the approximation of large-order FIR filters and allows the usage of arbitrarily shaped weighting functions. It is shown that our method can successfully be employed to achieve a uniform approximation