Design of linear phase FIR filters using fractional derivative constraints

In this paper, the designs of linear phase FIR filters using fractional derivative constraints are investigated. First, the definition of fractional derivative is reviewed briefly. Then, the linear phase FIR filters are designed by minimizing integral squares error under the constraint that the ideal response and actual response have several same fractional derivatives at the prescribed frequency point. Next, the fractional maximally flat FIR filters are designed by letting the number of fractional derivative constraints be equal to the number of filter coefficients. Finally, numerical examples are demonstrated to show that the proposed method has larger design flexibility than the conventional integer derivative constrained methods.     

Oversampled sigma-delta LMS adaptive FIR filters

Two filter designs for adaptive least mean squares (LMS) filtering with sigma-delta modulated input signals are described. One implementation is multibit multiplier-free and operates entirely at the oversampling frequency of the sigma-delta signals, in the other design only the FIR filter operates at the oversampled frequency while the adaptive filtering algorithm is performed at the Nyquist rate. To circumvent any aliasing problems that may be caused by the downsampling process in the architecture and ensure convergence of the adaptive FIR filter. It is necessary to attenuate the high-frequency sigma-delta quantisation noise that is present. To perform this task a multiplier-free, multistage IIR filter structure is used that requires considerably fewer computations than an equivalent FIR filter. The two adaptive LMS filter designs are analysed and their performance is compared with a conventional PCM system in terms of achievable minimum MSE and adaptation speed     

Design of FIR linear phase filters with discrete coefficients usingHopfield neural networks

A novel method is presented for designing FIR linear phase filters with discrete coefficients using Hopfield neural networks. The proposed procedure is based on the minimisation of the energy function of the Hopfield neural network, and can produce a good solution to the design of FIR linear phase filters with discrete coefficients     

Design of nonuniformly spaced linear-phase FIR filters using mixedinteger linear programming

An optimization problem for designing a nonuniformly spaced linear-phase FIR filter with minimal complexity is formulated and solved by mixed integer linear programming (MILP). Examples illustrate that the proposed method is useful for designing a wide range of filter types and can outperform subset selection-based design methods     

Efficient determination of FIR Wiener filters with linear phase

The letter deals with the efficient determination of FIR Wiener filters with linear phase. This task is achieved by exploiting the Toeplitz-plus-Hankel structure which is imposed on the normal equations matrix by the phase linearity constraint and the stationarity assumption. It is shown that the design of these filters is ultimately reduced to the computation of optimum FIR Wiener filters by Levinson's algorithm.     

Relations between thek-dimensional unconstrained and linear phase FIR Wiener filters

In this note, we show that thek-dimensional linear phase FIR Wiener filter can be obtained from the unconstrained filter with a simple reverse and add operation. The relation between the linear phase and unconstrained phase filters is obtained also in the case of a multichannelk-dimensional system. In this case, the properties of the autocorrelation matrix do not allow the simplifications noted for the single channel case.     

Design of FIR digital filters using tapped cascaded FIR Subfilters

This paper considers the design of an FIR digital filter by interconnecting a number of identical FIR subfilters with the aid of a few additional multipliers and adders. The overall structure is in the form of a tapped cascaded FIR subfilters. A composite method to determine the tapping coefficients along with the coefficients of the subfilter to approximate overall frequency response characteristic is proposed. Several numerical examples illustrating the proposed method are included.     

Bit-serial VLSI implementation of delayed LMS adaptive FIR filters

The delayed least-mean-square (DLMS) algorithm is useful for adaptive finite impulse response (FIR) filtering applications where high throughput rates are required. In the paper, a bit-serial bit-level systolic array based on new schemes for multiplication and inner-product computation is presented to implement DLMS adaptive N-tap FIR filters. The architecture is highly regular, modular, and thus well-suited to VLSI implementation. It has an efficiency of 100% and a throughput rate of one filter output per 2B cycles, where B is the word length of input data. In addition, the proposed array uses a small delay of [(4B+N/2+4)/2B] in the filter coefficient adaptation, where [x] is the smallest integer greater than or equal to x. This ensures that the DLMS algorithm can have good performance under proper selection of the step size. Based on a conservative design technique of static complementary metal oxide semiconductor (CMOS) logic, it is shown that the proposed system can be realized in a single chip for most practical applications     

Offset compensation scheme for analogue LMS adaptive FIR filters

Offset voltage in the adapting part of an analogue LMS adaptive filter, caused by clock feedthrough, causes serious degradation of the convergence and error performance of the filter. A compensation scheme for the clock-induced offset is described. Simulation results at both algorithmic and circuit level are presented.<>     

A comparison of LTE channelizers implemented with linear phase m-path recursive filters and FIR filters

Cell sites repeaters may receive a composite signal containing a mix of long term evolution channels with bandwidths of 5, 10, 15, and 20 MHz and be required to rearrange the frequency plan of the channels or to drop and insert specific channels prior to transmitting the altered composite signal. The straight forward approach to this task is to down-convert, and down-sample each channel in the mix and then up-sample and up-convert and merge the new traffic mix. The filters applied to the up and down conversion task as well as the up and down sampling task would likely be linear phase finite impulse response (FIR) filters because of the ease with which the resampling task can be embedded in the filtering task. We present an alternate filter structure formed from linear phase recursive filters and compare their performance and computational complexity with their FIR filter counterparts. We show that the recursive filter version of the channel extractor requires significantly few arithmetic operations and actually outperforms the non-recursive version as demonstrated by the error vector magnitude of the two options.     

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 transformation method, methods for the design of a filter having nth-order tangency at both ends (0, π) are also developed. This is an extension of Vaidynathan's method (1985) and the proposed transformation method. The advantages of the method are that the resulting filters have very flat passbands and the stopbands are computationally efficient.     

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。     

A design algorithm for optimal low-pass nonlinear phase FIR digital filters

The transfer function of the low-pass nonlinear phase finite impulse response (NLPFIR) digital filter is decomposed into a nonlinear phase part and a linear phase part. An algorithm is proposed to iteratively design the magnitude of the linear phase part and the squared magnitude of the nonlinear phase part by directly calling the Remez algorithm of McClellan, et al. [1]. In the design of the nonlinear phase part, we assume that the linearity constraint on the phase is dropped but the phase response is not specified. A scheme is incorporated into our algorithm so that it can design the filter with the desired ripple ratio. This approach also leads to a method for finding the minimum ripple ratio for the given orders of the two parts and band edges of the filters. The filters with ripple ratio larger than this minimum value can be designed by our algorithm and neither passband nor stopband ripples are required to be prescribed. Analysis of roundoff noise reveals that the cascade filter implementation usually needs higher wordlengths than its direct for counterpart for the same roundoff noise performance.     

Design of optimal minimum phase FIR filters by direct factorization

An improved method of designing optimal minimum phase FIR filters by directly finding zeros is proposed. The zeros off the unit circle are found by an efficient special purpose root-finding algorithm without deflation. The proposed algorithm utilizes the passband minimum ripple frequencies to establish the initial points, and employs a modified Newton's iteration to find the accurate initial points for a standard Newton's iteration. We show, with examples, that the proposed algorithm can be used to design very long filters (L = 325) with very high stopband attenuations.     

Description of FIR digital filters in the form of parallelconnection of linear phase FIRs

The authors aim to show that FIR digital filters can be described in the form of parallel connection of linear phase FIR digital filters. This representation method may be applicable to FIR digital filter design problems, reducing it to linear phase FIR digital filter design problems     

Design of complex FIR filters using semiinfinite quadraticoptimisation techniques

A new method is presented for complex FIR filter design. This method formulates the FIR filter design as a semi-infinite quadratic optimisation (SIQO) problem, in which the mean squared error between the desired response and the designed filter is minimised and a set of linear inequality constraints is used to ensure that the peak gain in the stopband satisfies the prescribed specifications. Simulation is used to illustrate the effectiveness of the proposed method     

Design of linear phase M-channel perfect reconstruction FIR filterbanks

We propose two approaches to design M channel nonparaunitary filter banks that satisfy perfect reconstruction (PR) and linear phase (LP) properties. In the first approach, the PR condition is imposed on only a high-pass filter. Although this method does not require nonlinear optimization, it has a demerit in that the order of a high-pass filter becomes high. In the second approach, two filters are optimized simultaneously using a Lagrange-Newton method. We can design PR filter banks that have the same length. The PR constraint is also formulated as a linear and nonlinear equation of the analysis filter coefficients. Finally, some design examples are included     

Throughput-maximizing FIR transmit filters for linear dispersivechannels

Optimum finite-impulse response transmit filters for symbol-by-symbol transmission on linear dispersive additive Gaussian noise channels are derived by maximizing the channel throughput, subject to a fixed average input energy constraint. This maximized throughput is compared to that achievable with water-pour and flat transmit filters. The effect of transmit filter optimization on the receiver performance is investigated by considering the popular minimum mean-square error decision-feedback equalizer receiver structure     

Design of nonrecursive digital filters with linear phase

A new class of selective nonrecursive digital filters with independently prescribed equiripple passband and stopband attenuation and linear phase is obtained by numerical solution of a set of nonlinear equations. Some examples are given, and a comparison is made of the new solutions and those previously known.     

Design of sharp linear-phase FIR bandstop filters using the frequency-response-masking technique

A novel computationally efficient realization of sharp linear-phase finite impulse response (FIR) bandstop filters is proposed. The synthesis scheme for the bandstop filters is derived from variations of the frequency-response-masking technique. Five realization structures are presented in this paper for the synthesis of five different classes of bandstop filters. Approximate expressions for the optimal value of the impulse response up-sampling ratio (M) and the corresponding number of multipliers are derived.