Design Of Linear-phase Digital Filters Research Articles

Applications of simulated annealing for the design of special digital filters

The authors describe the salient features of using a simulated annealing (SA) algorithm in the context of designing digital filters with coefficient values expressed as the sum of power of two. A procedure for linear phase digital filter design, using this algorithm, is presented and tested, yielding results as good as those for known optimal methods. The algorithm is then applied to the design of Nyquist filters, optimizing at the same time both frequency response and intersymbol interference, and to the design of cascade form finite-impulse-response (FIR) filters. The drawback of using SA is that the computation time is on the order of 1-2 h for each filter design, on the Sun 3/60. However, this was more than compensated by the versatility of the new algorithm, which can be used to design filters with multiple constraints. >

Design of FIR digital filters using prescribed subfilters

A method for the design of linear-phase digital filters by the tapped cascaded interconnection of identical subfilters is presented. The method is an extension of the method proposed by Saramaki (1987). An example is given to show that the number of distinct multipliers of the filter determined by the proposed method is less than that of filters determined by Saramaki's method (1987). We also consider the case in which the subfilters are determined by multiple use of a single filter. In particular, if we can make the subfilters multiplierless then the number or multiplications per sample required to implement the overall filter is less than that required by the direct-form minimax method. Methods for the design of computationally efficient filters are also developed based on the proposed transformation method. The multiplication rate of the overall filter is the same as that of the prototype filter. It is very low as compared to that designed by the equivalent direct-form minimax method. With the proposed...

Optimal linear phase digital filter design by one-phase linear programming

An improved linear programming algorithm for the design of optimal linear-phase FIR filters with extra time-domain or frequency-domain constraints is presented. After stating the problem as involving the minimization of a linear function of filter parameters with linear constraints, a method is given for choosing an initial basic feasible solution of the dual problem that does not require the introduction of artificial variables. This significantly reduces the number of iterations of the revised simplex algorithm needed to reach the optimal solution.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A State of the Art Survey on Linear Phase Digital Filter Design

A State of the Art Survey on Linear Phase Digital Filter Design

A Multiple Exchange Algorithm for Calculation of Best Restricted Approximations

In this paper, a multiple exchange algorithm for calculation of best restricted approximations is presented and its convergence is proved. The algorithm presented is an extension of the single exchange algorithm for calculation of best restricted approximations which was recently given by Taylor and Winter [1]. Based on computational experience with a class of approximation problems encountered in linear phase digital filter design, a comparison of single exchange and multiple exchange convergence rates and C.P.U. times per iteration is given.

Invariant-sinusoid approximation method for recursive digital filters

An approximation method for recursive digital filters is described. Given an analogue filter, a corresponding digital filter can be derived such that an invariant sinusoidal response is maintained. The method is shown to preserve the phase response of the analogue filter, and is thus suitable for the design of linear-phase digital filters.

Linear phase digital filter design

The results of an investigation of linear phase digital filters are presented. It was determined that stable filters of this type are necessarily nonrecursive. The corresponding transfer function is presented in a general form in terms of basic z-plane pole and zero configurations. The design of digital filters of this form is accomplished by approximating a desired frequency function by one of four types of Fourier series. The types of series correspond to the forms of the z transfer function polynomial, which is either a mirror-image polynomial or a negative mirror-image polynomial, and either even or odd order.