设计ⅡR数字滤波器的遗传优化算法

提出了ⅡＲ数字滤波器设计的遗传优化法。这是一种模拟自然遗传和达尔文进化理论的随机并行优化算法。首先，详细描述了遗传算法并给出了计算步骤，然后将遗传算法用于ⅡＲ数字滤波器的优化设计，最后给出了模拟计算结果。     

滤波器电路的计算机辅助设计综述

本文综述了集总参数元件滤波器电路的计算机辅助设计的发展及目前的状况。首先讨论了滤波器传输函数的逼近及机助设计情况，列出了有关带有程序清单的参考文献；然后指出了ＬＣ滤波器机助设计中的难点及解决的办法，并给出了简单滤波器设计的显式公式。对于有源滤波器的机助设计，文中分析了有源滤波器ＣＡＤ的发展及现状，阐述了开发有源滤波器设计程序所遵循的原则，对于数字滤波器，文中回顾了ＩＩＲ和ＦＩＲ数字滤波器机助设计的情况，并阐明了正交镜像滤波器的机助设计方法。     

基于巴特沃斯逼近的二维IIR数字滤波器的设计

本文给出了一种基于巴特沃斯逼近的二维ＩＩＲ数字滤波器的设计方法，得到了由基本的全通节级联，并联实现的各种二维滤波器函数，包括，镜象对称互补滤波器，扇形滤波器和具有任意矩形通、阻带的滤波器，结果表明，这种实现结构具有通有灵敏度低、滤波器系数少的优点，并且由于巴特沃斯逼近的最大平坦性，得到的滤波器具有良好的相位特性。     

基于遗传算法的同轴腔EMI滤波器的优化设计

在简要介绍一种新的宽频带电磁干扰(EMI)滤波器设计思路的基础上。重点论述了高频段同轴腔EMI滤波器的设计方法。本文首先给出了高频段分布参数元件滤波器的设计原理，然后利用遗传算法对高频段同轴腔EMI滤波器进行优化设计，获取优化值，并给出了精确的设计结果，最后给出了仿真结果。     

基于频率采样技术的FIR数字滤波器优化设计

本文提出了一种FIR数字滤波器满意优化设计方法，将滤波器过渡带样本值作为优化变量，通过设计通带、过渡带和阻带性能指标满意度函数和综合满意度函数，构造出满意优化模型，并用本文提出的新量子遗传算法搜索满意解，FIR高通和带阻数字滤波器的设计结果表明，采用满意优化方法设计的FIR滤波器的性能优于传统方法。     

基于改进遗传量子算法的FIR数字滤波器设计

采用改进遗传量子算法(IGQA)进行FIR数字滤波器的优化设计,将滤波器的过渡带样本值作为变量进行优化,解决了传统方法(查表法)不能保证数据最优的问题。针对遗传量子算法(GQA)在优化连续多峰函数时易出现早熟的问题,提出一种改进遗传量子算法(IGQA),典型函数测试表明,IGQA的性能优于GQA和其它几种遗传算法,收敛速度快,全局寻优能力强,能有效地克服早熟现象。采用IGQA优化设计的FIR数字低通和带通滤波器的性能较查表法得到了很大改善。     

无限冲击响应数字滤波器设计软件

本文介绍了无限冲击响应（ＩＩＲ）数字滤波器设计软件的功能和使用方法，重点介绍了如何利用计算机仿真进行指标验证，最后举例说明该软件的使用情况。     

一种人工神经网络自适应IIR滤波器

本文提出了一种人工神经网络自适应ＩＩＲ滤波器，这种自适应ＩＩＲ滤波器采用并联型结构，用人工神经网络实现，并保证系统在自适应过程中的稳定性，从而得到了一种稳定的、高度并行的自适应ＩＩＲ滤波器，从根本上改变了以往的串行数值迭代系统，使滤波器自适应过程仅需要几个微秒就可以完成。从而有可能用神经自适应系统完成对快速变化信号的实时处理。本文给出了计算机模拟的结果，理论和模拟结果均表明该结构是稳定的，收敛速度也有明显增加。     

线性相位二维跳耦型数字滤波器组设计及其在图像子带编码中的应用

本文提出了一种新的二维递归数字滤波器组－二维跳耦型数字滤波器组的设计与实现方法。这种数字滤波器组的特点为：因果型－可用于实时图像分解与重构；线性相位－可避免传统的二维ＩＩＲ滤波引起的图像的相位畸变，非线性条件下稳定－有限字长实现二维数字滤波器组时，不存在溢出或极限环振荡，实际的图像处理实验证明，本文提出的设计理论及实现方法是正确的，有效的，可行的。     

基于遗传退火算法的MTI 滤波器设计方法

动目标显示(MTI)是雷达杂波抑制的重要技术之一,MTI 滤波器系数和脉冲参差比设计对MTI 的抗杂波性能至关重要。遗传退火算法将模拟退火算法过程溶入遗传算法,同时克服了遗传算法容易陷入局部最优和模拟退火算法收敛速度慢的缺点。文中介绍了一种将遗传退火算法应用于MTI 滤波器的设计方法,该方法可找到最优MTI 滤波器。实验结果表明,针对给定的MTI 滤波器设计要求,该方法能快速完成优化遍历,优化后滤波器性能提升明显。     

Design of IIR digital filters based on eigenvalue problem

This paper presents a new method for designing IIR digital filters with optimum magnitude response in the Chebyshev sense and different order numerator and denominator. The proposed procedure is based on the formulation of a generalized eigenvalue problem by using Remez exchange algorithm. Since there exist more than one eigenvalue in the general eigenvalue problem, we introduce a very simple selection rule for the eigenvalue to be sought for where the rational interpolation is performed if and only if the positive minimum eigenvalue is chosen. Therefore, the solution of the rational interpolation problem can be obtained by computing only one eigenvector corresponding to the positive minimum eigenvalue, and the optimal filter coefficients are easily obtained through a few iterations. The design algorithm proposed in this paper not only retains the speed inherent in the Remez exchange algorithm but also simplifies the interpolation step because it has been reduced to the computation of the positive minimum eigenvalue. Some properties of the filters such as lowpass filters, bandpass filters, and so on are discussed, and several design examples are presented to demonstrate the effectiveness of this method     

数字滤波器的近似等波纹设计法

本文证明了数字滤波器的自适应设计法等价于MMSE设计法，并提出用幅度误差函数对代价函数进行自适应迭代的算法达到近似等滤纹数字滤波器的自适应设计法．实验证明该设计方法简单有效，适合用于滤波器的工程设计。     

Approximate Time-Variable Coherence Analysis of Multichannel Signals

We present a new method for signal extraction from noisy multichannel epileptic seizure onset EEG signals. These signals are non-stationary which makes time-invariant filtering unsuitable. The new method assumes a signal model and performs denoising by filtering the signal of each channel using a time-variable filter which is an estimate of the Wiener filter. The approximate Wiener filters are obtained using the time-frequency coherence functions between all channel pairs, and a fix-point algorithm. We estimate the coherence functions using the multiple window method, after which the fix-point algorithm is applied. Simulations indicate that this method improves upon its restriction to assumed stationary signals for realistically non-stationary data, in terms of mean square error, and we show that it can also be used for time-frequency representation of noisy multichannel signals. The method was applied to two epileptic seizure onset signals, and it turned out that the most informative output of the method are the filters themselves studied in the time-frequency domain. They seem to reveal hidden features of the epileptic signal which are otherwise invisible. This algorithm can be used as preprocessing for seizure onset EEG signals prior to time-frequency representation and manual or algorithmic pattern classification.     

FIR Photonic Microwave Filter Design Employing Simulated Annealing Algorithm

Photonic microwave filters are important parts of fiber‐optic microwave/millimeter wave processing systems. In this paper, the synthesis problem of fiber‐optic FIR microwave filters is addressed and a novel method for designing photonic microwave filter employing a simulated annealing (SA) algorithm is proposed. The design problem of photonic microwave filter can be reduced to be a multi‐variable function optimization problem, which can be solved by a simulated annealing‐based algorithm. As an illustration of the application of SA to photonic microwave filter design, the synthesis of an optimizedFBG‐based photonic microwave filter is discussed. Numerical results show that the global minimum finding capability of SA makes it be an efficient way to design the photonic microwave filter. Numerical results also demonstrate that the proposed method can be applied to design different filtering systems with different constraints.     

MIMO-OFDM系统中一种基于自适应滤波的信道估计方法

该文提出了一种适用于MIMO-OFDM系统的基于自适应滤波器的信道估计方法,此方法在不需要任何信道统计信息的前提下,通过自适应滤波的方法对时变信道状态参数进行即时跟踪与估计。仿真结果表明该文提出的基于自适应滤波的信道估计方法,相比于不考虑噪声的基于LS算法的信道估计方法,MSE和BER性能均有很大的提高。其中基于LMS滤波器的信道估计方法具有计算复杂度小的特点;而基于RLS的信道估计方法具有收敛速度快,MSE和BER性能均优于基于LMS方法的特点。     

Up-scaling images in presence of salt and pepper noise

An image up-scaling algorithm that can also reduce salt and pepper noise is presented. The algorithm is based on a least mean square optimisation framework which trains on original images and the downsampled images corrupted by salt and pepper noise. Hybrid filters which are composed of structure-adaptive linear filters and rank-order filters are used. Experimental results show the effectiveness of the proposed algorithm.     

A fast square-rooting algorithm using a digital signal processor

The computation of square roots is required in signal processing applications, such as adaptive filtering using transversal filters or lattice filters, spectral estimation, and many other fields of engineering sciences. Actually, all the existing digital signal processors (DSP) have a multiplier-accumulator. We present a simple binary algorithm for square-rooting using a processor with multiplier. Only shifts, additions, and multiplications are used and unlike the Newton-Raphson approach, divisions are not necessary. The method can also be interesting for the computation of divisions. The algorithm has been implemented in 16-bit fixed-point arithmetic on a TMS32010 DSP processor. The computational requirements are compared with the Newton-Raphson method. The fixed-point code of the algorithm written in TMS32010 Assembly language is also given.     

Synthesis of extremal wavelet-generating filters using Gaussianquadrature

Orthogonal wavelets can be generated from finite impulse response quadrature mirror filters; these filters are also used in perfect reconstruction filter banks. This paper addresses the problem of efficiently synthesizing such filters. A class of extremal filters is defined by the property that their magnitude spectrum maximizes an integral criterion. It is found that these filters are characterized by their zeros on the unit circle, which frequently can be obtained from a set of orthogonal polynomials. A family of filters is constructed that minimize the subband aliasing energy and can generate wavelets with an arbitrary number of vanishing moments. The algorithm for generating these filters makes use of the Levinson recursions, Gaussian quadrature and a fast version of Euclid's algorithm. Similar to other methods for constructing quadrature mirror filters, the spectral factorization of a polynomial is the computationally expensive part of this algorithm     

A fast algorithm for designing stack filters

Stack filters are a class of nonlinear filters with excellent properties for signal restoration. Unfortunately, present algorithms for designing stack filters can only be used for small window sizes because of either their computational overhead or their serial nature. This paper presents a new adaptive algorithm for determining a stack filter that minimizes the mean absolute error criterion. The new algorithm retains the iterative nature of many current adaptive stack filtering algorithms, but significantly reduces the number of iterations required to converge to an optimal filter. This algorithm is faster than all currently available stack filter design algorithms, is simple to implement, and is shown in this paper to always converge to an optimal stack filter. Extensive comparisons between this new algorithm and all existing algorithms are provided. The comparisons are based both on the performance of the resulting filters and upon the time and space complexity of the algorithms. They demonstrate that the new algorithm has three advantages: it is faster than all other available algorithms; it can be used on standard workstations (SPARC 5 with 48 MB) to design filters with windows containing 20 or more points; and, its highly parallel structure allows very fast implementations on parallel machines. This new algorithm allows cascades of stack filters to be designed; stack filters with windows containing 72 points have been designed in a matter of minutes under this new approach.     

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