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.     

Least-squares design of IIR filters with prescribed magnitude andphase responses and a pole radius constraint

This paper presents a method for the frequency domain design of infinite impulse response (IIR) digital filters. The proposed method designs filters approximating prescribed magnitude and phase responses. IIR filters of this kind can have approximately linear-phase responses in their passbands, or they can equalize magnitude and phase responses of given systems. In many cases, these filters can be implemented with less memory and with fewer computations per output sample than equivalent finite impulse response (FIR) digital filters. An important feature of the proposed method is the possibility to specify a maximum radius for the poles of the designed rational transfer function. Consequently, stability can be guaranteed, and undesired effects of implementations using fixed-point arithmetic can be alleviated by restricting the poles to keep a prescribed distance from the unit circle. This is achieved by applying Rouche's theorem in the proposed design algorithm. We motivate the use of IIR filters with an unequal number of poles and zeros outside the origin of the complex plane. In order to satisfy simultaneous specifications on magnitude and phase responses, it is advantageous to use IIR filters with only a few poles outside the origin of the z-plane and an arbitrary number of zeros. Filters of this type are a compromise between IIR filters with optimum magnitude responses and phase-approximating FIR filters. We use design examples to compare filters designed by the proposed method to those obtained by other methods. In addition, we compare the proposed general IIR filters with other popular more specialized structures such as FIR filters and cascaded systems consisting of frequency-selective IIR filters and phase-equalizing allpass filters     

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     

FIR digital filter design techniques using weighted Chebyshev approximation

This paper discusses the various approaches to designing FIR digital filters using the theory of weighted Chebyshev approximation. The different design techniques are explained and compared on the basis of their capabilities and limitations. The relationships between filter parameters are briefly discussed for the case of low-pass filters. Extensions of the theory to the problems of magnitude and complex approximation are also included, as are some recent results on the design of two-dimensional FIR filters by transformation.     

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.     

Reduction of Symmetric Complex Filters

Due to their linear-phase property, symmetric filters are an interesting class of finite-impulse-response (FIR) filters. Moreover, symmetric FIR filters allow an efficient implementation. In this paper we extend the classical definition of Hermitian symmetry to a more general symmetry that is also applicable to complex filters. This symmetry is called generalized-Hermitian symmetry. We show the usefulness of this definition as it allows for a unified treatment of even and odd-length filters. Central in this paper is a theorem on the reduction of generalized-Hermitian-symmetric filters to Hermitian-symmetric filters, both with finite precision coefficients. A constructive proof of this theorem is presented and an associated procedure for reducing generalized-Hermitian-symmetric filters is derived. Two of the examples show the application of the reduction procedure and the achieved savings on arithmetic costs. Finally, all three examples show that a special instance of the generalized-Hermitian-symmetric filters with finite precision coefficients, may have lower arithmetic costs than the Hermitian-symmetric filter from which it is derived.     

Design of two-dimensional digital filters using singular-valuedecomposition and balanced approximation method

It is shown that the singular-value decomposition (SVD) of the sampled amplitude response of a two-dimensional (2-D) digital filter possesses a special structure: every singular vector is either mirror-image symmetric or antisymmetric with respect to its midpoint. Consequently, the SVD can be applied along with 1-D finite impulse response (FIR) techniques for the design of linear-phase 2-D filters with arbitrary prescribed amplitude responses which are symmetrical with respect to the origin of the (ωΨω₂) plane. The balanced approximation method is applied to linear-phase 2-D FIR filters of the type that may be obtained by using the SVD method. The method leads to economical and computationally efficient filters, usually infinite impulse response filters, which have prescribed amplitude responses and whose phase responses are approximately linear     

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。     

Entwurf nichtrekursiver Digitalfilter mit beliebigen Betrags- und Phasengängen

This paper presents an efficient multiple exchange algorithm for the frequency domain design of digital FIR filters with arbitrary magnitude and phase responses. The designed filters minimize theL ₂ norm of the weighted complex frequency domain error function subject to constraints on the resulting magnitude and phase errors. This general design criterion allows for an arbitrary trade-off between complexL ₂ approximation and Chebyshev approximation of given magnitude and phase responses. The optimization can be carried out by iteratively solving small quadratic programs. These linearly constrained subproblems can be solved using robust standard software.     

Complex IIR filter design through balance model reduction of FIRprototypes

The author extend the use of the balance model truncation and Hankel-norm optimal approximation to permit close approximation of complex FIR prototypes by IIR filters     

具有近似线性相位特性的多相波数字滤波器的设计

不考虑相位失真,而要求满足比较苛刻的振幅特性的时候,和FIR滤波器比较起来,采用 IIR 滤波器,计算量要小很多.但对某些IIR滤波器,采取适当的方法,也可以使其相位失真变得很小.本文提出一种新的设计方法,用来设计振幅响应完全满足设计要求,而相位特性用Chebyshev 近似来实现的多相波数字滤波器.这种方法的关键在于确定通带中的若干衰减零点.文中对需要的最小衰减零点数作了估计.实例表明,用这种方法设计的滤波器,时延小,相位特性非常接近线性.     

DESIGN OF POLYPHASE WAVE DIGITAL FILTERS WITH APPROXIMATELY LINEAR PHASE

It is well known that IIR digital filters require quite fewer computations,comparedwith FIR filters,in order to meet stringent magnitude specifications when the phase distortioncan be tolerated.An approximately linear phase,however,can be also obtained with the IIRfilter by making use of a technique without increasing the complexity.Based on a certain numberof attenuation zeros in the pass band,a new approach is developed for the design of polyphasewave digital filters with exact magnitude responses and Chebyshev approximation of the desiredphase responses.The minimum number of attenuation zeros is estimated,and some examples areincluded.     

3型FIR高阶多通带滤波器的自适应优化设计研究

本文详细讨论了3型线性相位滤波器幅频特性与正弦基神经网络算法间的关系，提出了该算法的收敛定理，给山了有限脉冲响应（FIR）高阶多通带滤波器自适应优化设计算法及实例。计算机仿真结果表明了该算法在FIR高阶多通带滤波器的有效性和优异性能。     

神经网络在4型FIR滤波器的优化设计研究

本文详细讨论了4型线性相位滤波器幅频特性与正弦基神经网络算法间的关系，提出并证明了该算法的收敛定理，给出了FIR高通滤波器和FIR带通滤波器优化设计实例。计算机仿真结果表明，该算法在FIR高通滤波器和带通滤波器的有效性和优异性能。     

二维线性相位FIR数字滤波器的优化设计

该文提出了一种用神经网络算法来设计二维线性相位数字滤波器的新方法。通过分析二维FIR线性相位滤波器的幅频响应特性,建立了神经网络算法。根据给定的幅频响应指标,按该算法可获得滤波器系数。为保证该算法的稳定性,提出并证明了该算法的收敛定理。文中给出了圆对称和矩形对称二维低通线性相位FIR数字滤波器优化设计实例。计算机仿真结果表明由该方法设计的二维数字滤波器,通带和阻带范围波动小,所需计算量非常少,稳定性强,因而是一种优异的设计方法。     

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     

On Chebyshev design of linear-phase FIR filters with frequency inequality constraints

The alternation theorem is the basis of the Remez algorithm for unconstrained Chebyshev design of finite-impulse response (FIR) filters. In this paper, we extend the alternation theorem to the inequality-constrained case and present an improved Remez algorithm for the design of minimax FIR filters with inequality constraints in frequency domain. Compared with existing algorithms, the presented algorithm has faster convergence rate and guaranteed optimal solutions.     

Complex coefficient fir digital filters

The complex FIR digital filter is a filter that has complex coefficients in itsZ-domain transfer function. The set of coefficients is determined, based on some criterion, to meet predefined requirements. On this basis, an algorithm is proposed for designing FIR digital filters with asymmetric amplitude response in conjunction with linear phase. Minimax approximation has been adopted for determining the set of coefficients, where the associated set of overdetermined linear equations is solved by using an efficient linear programming algorithm. Computer simulations show that, to meet prescribed specifications, the proposed design algorithm yields a complex FIR digital filter with the lowest order.     

Extended-window interpolation applied to digital filter design

This paper develops a procedure for the design of frequency-selective interpolation operators that can be computed and saved once and for all. These operators are used to design real-time digital operators: interpolators, FIR differentiators, IIR filters, and composed interpolation and filtering operators. Each real-time operator is a matrix relating sets of data points to sets of interpolated values. Since these matrices are characterized by low norms, they permit reduced-word implementations, and are suitable for real-time processing with array processors and massively parallel machines. The design of the interpolation operators uses windows that, unlike traditional approaches, extend beyond the data interval up to the length permitted by the dimensionality theorem. A new form of the dimensionality theorem is used to minimize the minimax interpolation error within a predetermined frequency range, which may be either the passband of the antialiasing filter or the passband of an analog prototype filter. The main application presented in the paper is the design of combined digital filters and interpolators, which will be referred to as interpolating filters. The frequency responses of such filters, as well as the interpolated time responses, almost coincide with those of the corresponding analog prototypes     

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.