解离散系数滤波器设计问题的分支定界算法

基于离散系数滤波器设计问题已有的半定规划松弛模型,利用文献[6]的方法给出了该问题的二次规划松弛模型,该模型能给出比半定规划模型更好的界,然后运用分支定界方法求解该模型。与随机扰动方法相比,该方法能得到一个性能更好的次优解,对于精度要求较高的滤波器设计问题,这种方法非常有效,并通过了仿真实验的证实。     

基于混沌粒子群优化算法的FIR数字滤波器设计

有限脉冲响应(FIR)数字滤波器的设计,实质上是一个多参数优化问题.将粒子群优化算法与混沌相结合来设计FIR数字滤波器,并用该方法设计了一个高通滤波器.与用Parks-McClellan算法设计得到的高通滤波器进行对比发现,基于混沌粒子群优化算法(CPSO)的FIR滤波器通带波动小,阻带衰减大,从而证明了该算法的有效性和优越性.     

A nearly optimum linear-phase digital FIR filters design

A new simple method to design linear-phase finite impulse response (FIR) digital filters, based on the steepest-descent optimization method, is presented in this paper. Starting from the specifications of the desired frequency response and a maximum approximation error a nearly optimum digital filter is obtained. Tests have shown that this method is alternative to other traditional ones such as Frequency Sampling and Parks–McClellan, mainly when other than brick wall frequency response is required as a desired frequency response.     

Hardware based genetic evolution of self-adaptive arbitrary response FIR filters

This work presents a hardware implementation of an FIR filter that is self-adaptive; that responds to arbitrary frequency response landscapes; that has built-in coefficient error tolerance capabilities; and that has a minimal adaptation latency. This hardware design is based on a heuristic genetic algorithm. Experimental results show that the proposed design is more efficient than non-evolutionary designs even for arbitrary response filters. As a byproduct, the paper also presents a novel flow for the complete hardware design of what is termed as an Evolutionary System on Chip (ESoC). With the inclusion of an evolutionary process, the ESoC is a new paradigm in modern System on Chip (SoC) designs. The ESoC methodology could be a very useful structured FPGA/ASIC implementation alternative in many practical applications of FIR filters.     

Optimal design of FIR linear phase digital filters via convex quadratic programming method

Many methods exist for designing FIR linear phase digital filters by using various optimization techniques. An optimization design method via the convex quadratic programming method is investigated in this paper. The aim of this method is to design digital filters with certain desired frequency responses that keep the passband ripple to a minimum while maintaining a balance between opposite characteristics of frequency responses, i.e. the narrow transition band and the great stopband attenuation. In order to verify the effectiveness of this method, low-pass filters are designed and comparison studies with other typical optimization methods are given.     

A novel singular spectrum analysis-based multi-objective approach for optimal FIR filter design using artificial bee colony algorithm

Neural Computing and Applications - Effective filter design plays an important role in signal processing applications. Multiple parameters must be considered to control the over-frequency response...     

基于RAG-n算法的低成本FIR滤波器实现

基于FIR数字滤波器多常数乘法的图表示法,利用MATLAB对RAG-n算法进行了实现。通过仿真该算法在大多数情况下都可以高效地解决加法器优化问题,有效降低了FIR滤波器常系数乘法的复杂度。在FPGA上用Verilog HDL语言对优化实例进行了实现,其综合结果表明,该方法可以有效减少逻辑单元的消耗,适用于低成本数字系统设计。     

A novel two-stage nonrecursive architecture for the design of generalized comb filters

This paper presents a novel two-stage class of decimation filters with superior spurious signal rejection performance around the so-called folding bands, i.e., frequency intervals whose signals get folded down to baseband due to decimation. The key idea to enhance signal rejection in the frequency domain lies on an effective way to place the zeros of a classical comb filter in the aforementioned folding bands. On the other hand, the paper provides a mathematical framework for designing two-stage multiplierless and nonrecursive structures of the proposed filters.Examples are provided to highlight the key steps in the design of the proposed filters. Moreover, the frequency behavior of the proposed filters in both baseband and stopband is compared with classical and generalized comb filters, and a droop compensator is proposed to counteract the passband distortion of the proposed filters.     

一种新的光纤捷联罗经算法设计

光纤捷联罗经比较传统平台罗经具有维护性好、可靠性高等优点。不同于传统的平台罗经算法,设计了一种适合于光纤捷联罗经使用的捷联罗经算法。算法引入一种全新的惯性坐标系,并以重力在该坐标系的投影解算出地理坐标系的转动;陀螺输出解算载体坐标系的转动,进一步得到载体的姿态值。设计了利用FIR数字滤波器滤波获得惯性坐标系重力投影的方法。最后仿真验证了算法编排和理论分析的正确性。     

一种高精度RF信号幅相检测电路的设计

本文首先谈论了高精度幅相检测方案的选择,以及带通滤波器的选择和AD8302的主要功能:然后结合f=13.56MH的频率设计了滤波器的参数分析仿真结果:以及AD8302的检测原理的分析.仿真和试验结果证明了这种电路的可行性.     

Empirical formula for designing a class of linear phase FIR single band PCLS filters

This paper presents an empirical formulation relating the filter length, the transition-band bandwidth, the cutoff frequency, the maximum passband-ripple magnitude, the maximum stopband-ripple magnitude and the total ripple energy of a class of linear phase finite impulse response (FIR) single band peak constrained least squares (PCLS) filters. Design examples are presented to demonstrate applications and accuracies of the presented formula.     

一种新型的分布式MEMS移相器的小型化设计

通过在共面波导信号线上贴敷低介电常数的薄层绝缘介质,使得MEMS金属桥与共面波导信号线在“关“态下形成MIM电容的方法,实现了提高“关““开“两种状态下的电容比,从而提高了单位长度上的相移量.与传统的设计方法相比,在达到同样相移量指标的情况下仅需少量的MEMS金属桥就可以实现,工作的可靠性得到提高,未封装MEMS移相器器件的总体尺寸可以减小60%左右,此外由于在“关“态下,金属桥直接贴敷在介质表面上而不会随着外界环境震动,因此移相器的相移精度显著的提高.     

FIR filters for online trajectory planning with time- and frequency-domain specifications

In this paper, the use of FIR (Finite Impulse Response) filters for planning minimum-time trajectories for robots or automatic machines under constraints of velocity, acceleration, etc. is presented and discussed. In particular, the relationship between multi-segment polynomial trajectories, i.e. trajectories composed of several polynomial segments, each one possibly characterized by constraints on one or more specific derivatives (i.e. velocity, acceleration, jerk, etc.), and FIR filters disposed in a cascade configuration is demonstrated and exploited in order to design a digital filter for online trajectory planning. The connection between analytic functions and dynamic filters allows a generalization of these trajectories, usually obtained by second- or third-order polynomial functions (e.g. trapezoidal velocity and double S velocity trajectories), to a generic order with only a modest increase of the complexity. As a matter of fact, the computation of trajectories with higher degree of continuity simply requires additional FIR filters in the chain. Moreover, the modular structure of the planner provides a direct frequency characterization of the motion law. In this way, it is possible to define the trajectories by considering constraints expressed in the frequency-domain besides the classical time-domain specifications, such as bounds on velocity, acceleration, and so on. Two examples illustrate the main features of the proposed trajectory planner, in particular with respect to the problems of multi-point trajectories generation and residual vibrations suppression.     

A novel genetic algorithm with different structure selection for circuit design optimization

In the traditional GA, the tournament selection for crossover and mutation is based on the fitness of individuals. This can make convergence easy, but some useful genes may be lost. In selection, as well as fitness, we consider the different structure of each individual compared with an elite one. Some individuals are selected with many different structures, and then crossover and mutation are performed from these to generate new individuals. In this way, the GA can increase diversification into search spaces so that it can find a better solution. One promising application of GA is evolvable hardware (EHW), which is a new research field to synthesize an optimal circuit. We propose an optimal circuit design by using a GA with a different structure selection (GAdss), and with a fitness function composed of circuit complexity, power, and signal delay. Its effectiveness is shown by simulations. From the results, we can see that the best elite fitness, the average fitness value of correct circuits, and the number of correct circuits with GAdss are better than with GA. The best case of optimal circuits generated by GAdss is 8.1% better in evaluation value than that by traditional GA.     

基于粒子群优化算法的自适应IIR滤波器设计

针对自适应无限冲激响应(infinite impulse response,IIR)数字滤波器的设计实质上是一个多参数优化问题,提出了一种用粒子群优化算法(particle swarm optimization,PSO)设计IIR数字滤波器的方法.将滤波器的设计问题转化为滤波器参数的优化问题,利用粒子群优化算法对整个参数空间进行高效并行搜索以获得参数的最优化,基于多个典型系统的随机数值仿真以及与最小二乘方法的比较研究,验证了该方法的有效性、全局性和对初值的鲁棒性.     

改进量子遗传算法及其在FIR滤波器设计中的应用

在对遗传算法和量子遗传算法分析和比较的基础上,提出了一种改进的量子遗传算法,并通过典型函数的优化验证各算法性能的优劣。将改进的量子遗传算法应用于优化求解频率取样法设计FIR滤波器过程中的过渡点样值,实验结果表明算法可以得到更佳的设计参数。     

On the coefficient quantization of Multiplicative FIR filters

This paper analyzes the effects of coefficient quantization of Multiplicative Finite Impulse Response (MFIR) filters used to approximate the behavior of pole filters. Statistical analysis, zero displacement sensitivity and frequency domain analysis are used as measures of the filter performance for different coefficient lengths. A practical expression for determining the required number of bits for the coefficient quantization as a function of a predefined maximum deviation in the magnitude response is proposed in combination with an alternative method based on a time domain analysis. The time domain analysis allows, for a specific pole approximation, to investigate the sensitivity of the MFIR structure to coefficient variations. The paper concludes that, statistically, the MFIR pole approximation filter does not require a larger number of quantization bits for its coefficients than the corresponding Infinite Impulse Response (IIR) filter.     

A novel hybrid immune algorithm for global optimization in design and manufacturing

This paper presents a new hybrid optimization approach based on immune algorithm and hill climbing local search algorithm. The purpose of the present research is to develop a new optimization approach for solving design and manufacturing optimization problems. This research is the first application of immune algorithm to the optimization of machining parameters in the literature. In order to evaluate the proposed optimization approach, single objective test problem, multi-objective I-beam and machine-tool optimization problems taken from the literature are solved. Finally, the hybrid approach is applied to a case study for milling operations to show its effectiveness in machining operations. The results of the hybrid approach for the case study are compared with those of genetic algorithm, the feasible direction method and handbook recommendation.     

一种基于离散傅立叶变换域相位和幅度的数字水印算法

将水印分别嵌入离散傅立叶变换(DFT)域的相位谱、幅度谱进行仿真实验,比较了两种算法在相同的嵌入失真下的鲁棒性,提出了相位幅度相结合的DFT域水印算法,算法在提取水印时不需要原始图像。实验证明,该相幅水印算法简单易行,具有很好的不觉察性,而且对图像的尺度变换、旋转攻击、噪声干扰、JPEG压缩以及滤波等都具有很强的鲁棒性。     

遗传算法在FIR窗函数设计中的应用

本文将遗传算法引入FIE的窗函数设计中,提出了窗函数可以由一系列离散的介于0－1的仅值来取代的思路。根据预期频率特性的指标要求,我们建立了窗权值的优化模型,并通过遗传算法来求解,所得的优化解将使对应FIE滤波器的频率特性较好地满足预期频率特性的要求。本设计方法简单,工作量小,具有高的灵活性和鲁棒性,数值实验表明了本方法的有效性。