进化规划用于自适应IIR滤波器的优化设计

针对自适应ＩＲ滤波器（ＡＩＲＦ）潜在的不稳定性和性能指标函数容易陷入局部极小点而导致性能下降等问题，本文将进化规划用于直接、并联、级联和格型结构的ＡＩＩＲＦ的优化设计。基于进化规划的自适应滤波算法不依赖于梯度信息，能够有效地实现ＡＩＩＲＦ参数的全局寻优。大量的仿真实验结果表明不同结构的ＡＩＲＦ用进化规划进行参数寻优，不仅解决了自适应滤波器性能指标函数容易陷入局部极小点的问题，亦解决了ＡＩＲＦ的稳定性问题。     

一种设计对数FIR数字滤波器的方法

本文提出了一种设计具有等波纹对数幅度响应的线性相位ＦＩＲ数字滤波器的方法,该设计方法以多次交换算法为基础。在给定通带与阻带误差比、通带误差和阻带误差三种情况下讨论该设计方法。介绍几个低通对数ＦＩＲ滤波器的设计例子,来说明该设计方法的效率。     

高阶FIR型正交镜像滤波器的设计9

本文计论了高阶ＦＩＲ型正交镜像滤波器的设计问题。根据ＦＩＲ正交镜像滤波器设计的基本原理，将高阶正交镜像滤波器的设计问题转换为单变量的优化设计问题。利用一维寻优的算法，可以设计出高阶ＦＩＲ型正交镜像滤波器。     

FIR数字滤波器设计的复数神经网络方法

ＦＩＲ滤波器的设计是数字信号处理中的一个重要问题,神经网络则在优化设计方面显示了其良好的应用前景,但目前大多数应用均限于实数神经网络的情形．本文针对ＦＩＲ数字滤波器的设计问题,构造了具有复数状态、输出、联接权和偏置输入的Ｈｏｐｆｉａｌｄ网络,给出了网络的计算能量函数,并证明了算法的收敛性．通过近似线性相位、非共轭对称频响ＦＩＲ滤波器的设计实例表明,本文的工作对推广复数神经网络的应用与寻求更为复杂的ＦＩＲ滤波器设计的新方法均作了有效的尝试．     

模块法设计FIR数字陷波器的一种新方法

在模块法设计ＦＩＲ数字滤波器的基础上，提出一种设计ＦＩＲ数字陷波器的新方法。该方法将数字陷波器等效成为一个全通滤波器减去一个由基本频率单元构成的点通滤波器，进而推导出计算数字陷波器冲激响应的数学公式。该方法具有公式简单、物理概念清晰，陷波点频率不受模块数取整的约束，便于连续控制陷波点频率的优点。与窗口法设计相比，在同等凹口宽度下具有阶数减半的优点。同时，该方法可以推广至带阻滤波器的设计。     

基于多项式分解的自适应FIR滤波器脉动结构

该文由多项式信号的并行表达得到一种ＦＩＲ滤波器并行结构，通过对ＦＩＲ滤波器并行结构的分析，提出了几种自适应ＦＩＲ滤波器的并行处理算法，同时给出了相应的脉动实现结构。     

一维线性相位FIR数字滤波器的领域最小平方误差设计方法

本文提出了一种设计一维线性相位ＦＩＲ数字滤波器的新方法。该方法采用的频域的最小平方误差函数使所求的增益特性逼近所希望的增益特性，其计算公式非常简单，并可设计任意形状增益特性的ＦＩＲ数字滤波器。设计产例表明提出的方法非常有效。     

最大SNR线性相位FIR数字滤波器的设计

本文介绍了用于最大信噪比（ＳＮＲ）有限脉冲响应（ＦＩＲ）数字滤波器设计的梯度算法。我们注意到，对特征值梯度的确定产东能从任何起始点得出决体最大值。文章中研究了用所提出的方法设计的线性相位低通、高通和带通滤波器的特性。既使当渺茫皮器长度相当小时，最大信噪比滤波器也能够保持相当好的滤波性能。该滤波器对已知功率谱的稳定信号和稳定噪声组成的混合信号处理方面具有较强的优越性。     

微波电路的时域设计方法

本文研究了几种微波电路和无件和ＦＩＲ数字滤波器的直接结构形式的内在关系。从而将ＦＩＲ数字滤波器的窗函数设计技术引用到微波电路的设计中，提出了这些微波电路的时域设计方法。该方法具有简捷，有闭合形式公式可循等优点，尤其适合于工程设计。     

FIR的FPGA设计

本文分析了ＦＩＲ滤波器的硬件实现技术,并结合ＱｕｉｃｋＲＡＭ系列ＦＰＧＡ的特点,给出了一个高效的设计方法。文中参考设计为一个３６Ｔａｐｓ ８Ｂｉｔｓ的１０ＭＨｚ采样速率的ＦＩＲ。     

Evolutionary Design of Digital Filters With Application to Subband Coding and Data Transmission

In this paper, two evolutionary programming (EP) algorithms (classical EP and fast EP) are applied to design prototype lowpass Finite Impulse Response filters for use in a modulated filterbank. The chosen filter design technique is based on frequency-sampling (where the Fourier transform magnitudes of the filter are the objective variables). Design is simplified by constraining most of these values, leaving only a small number of values in the filter transition band to be optimized. The EP algorithms were used to determine the optimum values for this subset of values. Since there is an additional monotonic constraint on the transition band values, a modification to the EP algorithms was developed called variable limits evolutionary programming. Results indicate that a) both EP algorithms were insensitive to initial conditions, and reliably found the minimum values of the chosen objective functions, and b) the designed prototype filters are suitable to obtain near-perfect reconstruction filter banks, offering quality parameters comparable or better than systems obtained using other techniques     

直接序列扩频通信中干扰抑制的进化规划自适应非线性滤波技术

进化规划（ＥｖｏｌｕｔｉｏｎａｒｙＰｒｏｇｒａｍｍｉｎｇ）是模拟生物界自然选择和变异机制的一种随机并行搜索优化算法。本文提出了应用于直接序列扩频通通信中窄带干扰抑制的基于进化规划的自适应非线性滤波技术，并与传统的自适应非线性滤波技术进行了比较，结果表明本文算法更优。不仅实现了自适应非线性滤波的全局寻优和快速收敛，而且提高了系统的稳定性，尤其对于极点靠近单位圆的ＡＲ模型信号干扰，滤波性能有较大的提高。     

A Maximum Likelihood Method for Estimating EEG Evoked Potentials

The problem of EEG evoked potential (EP) estimation is basically one of estimating a transient signal embedded in nonstationary mostly additive noise; and as such it is well suited to a nonstationary estimation approach utilizing, for example, the Kalman filter. The method presented in this paper is based on a model of the EEG response which is assumed to be the sum of the EP and independent correlated Gaussian noise representing the spontaneous EEG activity. The EP is assumed to vary in both shape and latency; the latter is assumed to be governed by some unspecified probability density; and no assumption on stationarity is needed for the noise. With the model described in state-space form, a Kalman filter is constructed, and the variance of the innovation process is derived; a maximum likelihood solution to the EP estimation problem is then obtained via this innovation process. The method was tested on simulated as well as real EEG data.     

匹配滤波器同步捕获技术FPGA设计

匹配滤波器在信号检测和通信系统的同步捕获中起着关键的作用。基于软件无线电思想,分析了匹配滤波器的基本原理,采用一种可编程的分布算术式匹配滤波器同步捕获技术,可用于直接序列扩频接收机。模块采用Altera公司的FPGA Cyclone II EP2C35F672进行设计,仅占用全部逻辑资源的1%。对设计中部分功能单元进行了ModelSim功能仿真,给出了数值实验结果。     

基于SoPC的FIR滤波器设计与实现

分析了FIR滤波器几种常见实现方法的原理与不足;提出一种基于SoPC的FIR滤波器设计;介绍了系统的设计流程及实现方法;结合Matlab给出FIR滤波器的仿真结果。整个设计以Altera公司现场可编程逻辑器芯片EP3C25E144CSN为核心,具有程序简单,调试方便的特点,有一定的实用价值及应用前景。     

基于FPGA的FIR滤波器的性能研究

目前FIR滤波器的一般设计方法比较繁琐,开发周期长,如果采用设计好的FIR滤波器的IP核,则开发效率大为提高。本方案基于Altera公司的Cyclone Ⅱ系列芯片EP2C8Q208C8N,首先利用MATLAB中的滤波器函数fir2得出需产生的FIR滤波器的系数,再导入FIR IP Core,成功完成了FIR数字滤波器的设计。另外分析了阶数与不均匀采样数据对FPGA资源的影响和对生成FIR滤波器的输出性能的影响,并将实际输出的幅频特性图与我们需要的幅频特性图相比较,验证生成的FIR数字滤波器的性能。     

Automatic detection of intraoperative neurological injury

Neurological injuries occurring during high-risk surgical procedures can be detected by monitoring intraoperative evoked potential signals. In this communication, an automatic injury detection algorithm is proposed in which the EP signal is modeled as a pole-zero filter and then the model parameters are applied as inputs to a classifier type neural network. A recognition rate of 96% is achieved using an experimental model of brain injury.     

Peak component latency-corrected average method for evokedpotential waveform estimation

A peak component latency-corrected average (PC-LCA) method consisting of three steps is presented for estimating the evoked potentials (EP) in the human brain. The present PC-LCA is essentially an alternative version of the original LCA method developed by McGillem et al. (1977, 1985). It first uses a time-varying adaptive filter as a preprocessor to suppress the ongoing EEG and to enhance the EP. Then, the statistics of mean latencies and amplitudes of the EP peak components are estimated by a peak detection and alignment procedure. The final waveform estimate is obtained by superimposing the estimated mean peak components on background information and subsequently fitting a truncated Fourier series using the fast Fourier transform (FFT). Consistent estimates of the EP peak component information are established based on asymptotic analysis of the PC-LCA. Finally, real-time implementation of the PC-LCA is considered, and the superior performance of the PC-LCA method is confirmed by detailed numerical results     

Evolutionary programming synthesis of optimal long-period fibergrating filters for EDFA gain flattening

An innovative long-period fiber grating (LPG) synthesis method based on the stochastic evolutionary programming (EP) algorithms is demonstrated to be effective for designing optimal LPG filters. Synthesis of a single-stage LPG filter for the entire C-band erbium-doped fiber amplifier (EDFA) gain flattening is used as an example to show the feasibility and the effectiveness of the proposed algorithm. To the best of our knowledge, this is the first demonstration that good EDFA gain flattening for the entire band can be achieved with a single-stage LPG filter that is properly designed     

基于FPGA的Kalman滤波器的设计

针对电路设计中经常碰到数据的噪声干扰现象,提出了一种Kalman滤波的FPGA实现方法。该方法采用了Ⅱ公司的高精度模数转换器ADS1251以及Altera公司的EPIC12,首先用卡尔曼滤波算法设计了一个滤波器,然后将该滤波器分解成简单的加、减、乘、除运算。通过基于FPGA平台的硬件与软件的合理设计,成功地实现了数据噪声的滤除设计,并通过实践仿真计算,验证了所实现滤波的有效性。