应用多重交换法设计具有κ个陷波频点的等波纹FIR陷波滤波器

本提出了一种设计等波纹线性相位FIR陷波滤波器的优化算法。首先介绍了线性相位FIR吸滤波器的四种情况，然后在此基础上设计了一种应用多重交换算法来处理心电信号的陷波滤波器。此算法相对于均方误差最小准则和最大误差最小化准则具有占用存储空间小和计算时间短的优点。     

通带可调相位 FIR 数字滤波器及其设计

常见的 FIR 数字滤波器大致可分为两类:一类是线性相位滤波器;另一类是极小相位滤波器,这两种类型的滤波器,其相位响应均不可调.第一种滤波器,其群延迟为((N-1)T)/2,其中 N 为滤波器长度,T 为采样周期.以 N=60,T=0.2秒的线性相位滤波器为例,它的相位响应为     

基于TMS320C 5410EVM 板FIR滤波器算法与设计方法研究

数字滤波器是语言、图象处理、模式识别以及谱分析中的基本运算的处理运算。本文研究DSP中有限冲击响应(FIR)滤波器的原理并结合TM320C5410EVM板介绍FIR滤波器设计方法以及DSP中FIR滤波嚣的实现方法。     

基于神经网络的FIR多阻带数字滤波器的设计及应用

针对电子测量系统中的工频50Hz及其二次三次谐波干扰，本文运用BP神经网络设计一个三阻带数字滤波器，利用神经网络权值与FIR数字滤波器脉冲响应之间的关系，得出所设计滤波器的脉冲响应。实验表明，与窗函数法设计的三阻带滤波器相比，基于神经网络的FIR三阻带滤波器具有明显的优越性。     

中心对称仿酉矩阵的构造及二元具有线性相位正交小波滤波器组的参数化

中心对称仿酉矩阵(简记为CSPM)在线性相位的小波滤波器组的构造中起着重要的作用,本文给出偶数阶CSPM的表达式,矩阵中的元素为二元一次多项式.基于已给出的CSPM,给出具有线性相位的二元正交小波滤波器组的参数化,通过选取不同的参数可以得到的具有线性相位的正交小波滤波器组.最后给出算例.     

一维参数化正交小波滤波器的解析性质与优化逼近

本文给出了一维参数化正交小波滤波器系数向量的解析表达式和它的递推计算公式,还给出了它的一阶变分及二阶变分公式．利用这些结果和最优化方法,给出了FIR正交小波滤波器的逼近和设计问题的优化模型和数值例子．     

具有线性相位的4带正交滤波器的参数化

该文得到了具有线性相位的4带正交尺度滤波器的参数化形式,同时给出了构造相应的小波滤波器的一个简单的构造方法.应用所给出的参数化形式,得到了具有紧支撑的对称正交的尺度函数,进而也获得了相应的小波.     

保结构算法的相位误差分析及其修正

辛算法和保能量算法是应用最为广泛的两种保结构算法.本文从相位误差的角度给出了他们的比较结果.我们针对线性动力系统,分别分析了基于Pade对角逼近给出的辛算法和基于平均向量场法得到的能量守恒算法的相位误差,并通过数值验证了分析结果.文章还给出了保结构算法相位误差的改进方法,并通过数值例子验证了方法的有效性.     

一种基于二进提升方案的医学图像增强

通过分析和研究二进提升方案,得到一种新的提升二进小波滤波器的构造方法.以新的B-样条二进小波作为初始二进小波滤波器,结合二维6 trous算法对原始医学图像进行多层分解,根据分解后系数特点,一方面对不同级数的高频系数利用单阈值和双阈值函数增强,对低频子带系数用线性拉升来扩大图像的整体对比度.另一方面结合消失矩条件,调整滤波器的提升参数,构造了具有线性相位、紧支撑、高阶消失矩及有限长的单位脉冲响应的提升二进小波,并将其与初始二进小波滤波器增强后图像进行比较.仿真结果表明提升后的滤波器对于对比度低、弱光照图像比初始滤波器的增强效果有了进一步提高,噪声放大问题有明显改善,更好地突出图像边缘特征、保留了图像更多细节信息.     

基于仿酉矩阵的紧支撑二元正交小波滤波器组的构造

高维小波是处理多维信号的有力工具,张量积和栅格结构的小波有其自身的特点,但在实际应用中,我们仍需要构造小波滤波器来满足特定情形下的需要以提高滤波的效果,而构造正交滤波器,在多相域里就等价于构造仿酉阵,在本文中,我们通过对仿酉矩阵的研究,证明二元一次对称的仿酉阵一定能够块对角化,利用这种性质,给出了不可分离的二元正交小波滤波器组及线性相位小波滤波器的构造,并给出了相应的例子．     

Fast algorithms for designing variable FIR notch filters

The paper presents fast algorithms for designing finite impulse response (FIR) notch filters. The aim is to design a digital FIR notch filter so that the magnitude of the filter has a deep notch at a specified frequency, and as the notch frequency changes, the filter coefficients should be able to track the notch fast in real time. The filter design problem is first converted into a convex optimization problem in the autocorrelation domain. The frequency response of the autocorrelation of the filter impulse response is compared with the desired filter response and the integral square error is minimized with respect to the unknown autocorrelation coefficients. Spectral factorization is used to calculate the coefficients of the filter. In the optimization process, the computational advantage is obtained by exploiting the structure of the Hessian matrix which consists of a Toeplitz plus a Hankel matrix. Two methods have been used for solving the Toeplitz‐plus‐Hankel system of equations. In the first method, the computational time is reduced by using Block–Levinson's recursion for solving the Toeplitz‐plus‐Hankel system of matrices. In the second method, the conjugate gradient method with different preconditioners is used to solve the system. Comparative studies demonstrate the computational advantages of the latter. Both these algorithms have been used to obtain the autocorrelation coefficients of notch filters with different orders. The original filter coefficients are found by spectral factorization and each of these filters have been tested for filtering synthetic as well as real‐life signals. Copyright © 2007 John Wiley & Sons, Ltd.     

Fast integral wavelet transform on a dense set of the time-scale domain

Summary. The objective of this paper is to introduce a fast algorithm for computing the integral wavelet transform (IWT) on a dense set of points in the time-scale domain. By applying the duality principle and using a compactly supported spline-wavelet as the analyzing wavelet, this fast integral wavelet transform (FIWT) is realized by applying only FIR (moving average) operations, and can be implemented in parallel. Since this computational procedure is based on a local optimal-order spline interpolation scheme and the FIR filters are exact, the IWT values so obtained are guaranteed to have zero moments up to the order of the cardinal spline functions. The semi-orthogonal (s.o.) spline-wavelets used here cannot be replaced by any other biorthogonal wavelet (spline or otherwise) which is not s.o., since the duality principle must be applied to some subspace of the multiresolution analysis under consideration. In contrast with the existing procedures based on direct numerical integration or an FFT-based multi-voice per octave scheme, the computational complexity of our FIWT algorithm does not increase with the increasing number of values of the scale parameter. Received March 3, 1994     

Integer solution of a set of bilinear equations

An efficient method for a design of transmultiplexer filters is suggested. The perfect reconstruction conditions lead to the bilinear equations for FIR filters coefficients. The method of solving these equations results from the presented theorem. Usefulness of the algorithm in fixed-point arithmetic is the crucial issue. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Application of Rouche’s theorem for MP filter design

The method for the minimum-phase (MP) finite impulse response (FIR) filter design, based on Rouche’s theorem from complex analysis is presented here. The filter is designed directly from a given specification. The method uses the cosine filters and the sharpening technique resulting in a multiplierless filter.     

Differential Evolution with Wavelet Mutation in Digital Finite Impulse Response Filter Design

This paper proposes one novel algorithm called differential evolution with wavelet mutation for the optimal design of linear phase finite impulse response filters. For comparative performance study, the Parks–McClellan algorithm and some evolutionary algorithms like the real coded genetic algorithm, conventional particle swarm optimization, and conventional differential evolution have also been applied.     

N DIMENSIONAL FINITE WAVELET FILTERS

In this paper, a large class of n dimensional orthogonal and biorthognal wavelet filters(lowpass and highpass) are presented in explicit expression. We also characterize orthogonal filters with linear phase in this case. Some examples are also given, including non separable orhogonal and biorthogonal filters with linear phase.     

Construction of Two-Dimensional Compactly Supported Orthogonal Wavelets Filters with Linear Phase

In this paper, a large class of two-dimensional orthogonal wavelet filters, (lowpass and highpass), are presented in explicit expression. We also characterize the filters with linear phase in this case. Some examples are also given, including non-separable filters with linear phase. Received September 28, 1999, Accepted July 24, 2000     

A new approach to the weighted peak-constrained least-square error FIR digital filter optimal design problem

This paper deals with the design of linear-phase finite impulse response (FIR) digital filters using weighted peak-constrained least-squares (PCLS) optimization. The PCLS error design problem is formulated as a quadratically constrained quadratic semi-infinite programming problem. An exchange algorithm with a new exchange rule is proposed to solve the problem. The algorithm provides the approximate optimal solution after a finite number of iterations. In particular, the subproblem solved at each iteration is a quadratically constrained quadratic programming. We can rewrite it as a conic optimization problem solvable in polynomial time. For illustration, numerical examples are solved using the proposed algorithm.