Incorporation of Reduced Full Adder and Half Adder into Wallace Multiplier and Improved Carry-Save Adder for Digital FIR Filter

Improvement of digital FIR filter is vital in the field of Digital Signal Processing in order to reduce the area, delay and power. Multiplication and Accumulation (MAC) unit of Finite Impulse Response (FIR) filter has been designed using efficient multiplier and adder circuits for optimized APT (Area,Power and Timing) product. In this paper, the design of direct form FIR filter with efficient MAC unit has been presented. Initially, full adder and half adder structures are shrunk down by reducing number of gates. These compact full adder and half adder structures are incorporated into Wallace Multiplier and Improved Carry-Save Adder. The proposed 16-bit Carry-Save Adder has been improved by splitting into four parallel phases. Consequently the delay of enhanced Carry- Save Adder is reduced. Generation of carry output is performed using number of OR gates in a sequential manner. All these enhanced architectures are incorporated into the Digital FIR Filter to reduce the area, delay and power utilization.

FPGA-Based Efficient Programmable Polyphase FIR Filter

The modelling, design and implementation of a high-speed programmable polyphase finite impulse response (FIR) filter with field programmable gate array (FPGA) technology are described. This FIR filter can run automatically according to the programmable configuration word including symmetry/asymmetry, odd/even taps, from 32 taps up to 256 taps. The filter with 12 bit signal and 12 bit coefficient word-length has been realized on a Xilinx VirtexⅡ-v1500 device and operates at the maximum sampling frequency of (160 MHz.)

Indoor INS/UWB-based Human Localization With Missing Data Utilizing Predictive UFIR Filtering

A combined algorithm for the loosely fused ultra wide band(UWB)and inertial navigation system(INS)-based measurements is designed under the indoor human navigation conditions with missing data.The scheme proposed fuses the INS-and UWB-derived positions via a data fusion filter.Since the UWB signal is prone to drift in indoor environments and its outage highly affects the integrated scheme reliability,we also consider the missing data problem in UWB measurements.To overcome this problem,the loosely-coupled INS/UWB-integrated scheme is augmented with a prediction option based on the predictive unbiased finite impulse response(UFIR)fusion filter.We show experimentally that,the standard UFIR fusion filter has higher robustness than the Kalman filter.It is also shown that the predictive UFIR fusion filter is able to produce an acceptable navigation accuracy under temporary missing UWB-data.

Digital FIR filter design for bio-signal processing system

Recently,real-time processing systems for bio-signal of the muscles generated by the movement of the user have been developed.Finite impulse response(FIR)filter for bio-signal processing in bio-signal process systems is composed of multiple multiplier and adder of high-area.This makes the chip area increase significantly.To solve this problem,a low-area digital FIR filter is proposed in this paper,which can reduce the chip area.

DAPSO and PSO-VAF in Linear Phase Digital Low Pass FIR Filter Design

Digital filters play a key role in the field of digital signal processing. This paper presents a linear phase digital low pass finite impulse response (FIR) filter design using particle swarm optimization and its two new variants, dynamic and adjustable particle swarm optimization (DAPSO) and particle swarm optimization with variable acceleration factor (PSO-VAF) and illustrates the superiority of the PSO-VAF method over PSO based methods. Two fitness functions are considered. The fitness1 is used to find the possible minimum ripples in pass band and stop band in case of PSO, DAPSO and PSO-VAF. Fitness2 is able to control the ripples in both bands separately. A comparison of simulation results demonstrates the performance of PSO and its methods in designing digital low pass FIR filters.

High-Performance FIR Filter Implementation Using Anurupye Vedic Multiplier

In this, today’s world immeasurable analysis goes within the field of communication and signal processing applications. The FIR filter is mostly employed in filtering applications to enhance the quality of the signal. In any processor, the performance of the system is based on the speed of the multiplier unit involved in its operation. Since multiplier forms the indispensable building blocks of the FIR filter system. Its performance has contributed in determining the execution of the FIR filter system. Also, due to the tremendous development in the technology, many approaches such as an array, Vedic methods are made to speed up the multiplier computations. The problem in speed-up operation and resource utilization of hardware with all the conventional methods due to the critical path found in partial products has to be optimized using proposed method. This paper presents the implementation and execution of a FIR Filter design using Anurupye multiplier. Here the FIR filter is examined by using various multiplier algorithms such as Anurupye, Urdhava Tiryagbhyam, and array multipliers. The FIR filter is simulated for analyzing delay;area and power are meted out and lessened by utilizing proposed Anurupye multiplier. The FIR filter design utilizing proposed multiplier offers delay around 18.99 and only 4% of LUT slice utilization compared to existing methods. This architecture is coded in VHDL, simulated using the ModelSim and synthesized with Xilinx.

基于FIR-Stacking的刀具磨损预测

针对铣刀加工工件时传感器信号存在噪声、单一传统机器学习模型预测效果不理想的问题,提出一种基于自适应FIR滤波器和Stacking集成模型的刀具磨损预测方法。首先,采用自适应FIR滤波器去噪,计算时域、频域和时频域常用统计量作为信号特征,并对同一信号的多源信号特征进行拼接,经Pearson相关系数筛选保留相关系数大于0.2的特征;最后,以LightGBM、支持向量回归(support vector regression,SVR)、多层感知机(multilayer perceptron,MLP)作为基模型,Lasso作为元模型,构建Stacking集成模型进行刀具磨损预测。使用铣削加工数据集进行验证,结果表明该方法可有效提高预测准确性。

带FIR滤波的非线性滑动平均动态软测量模型

非线性滑动平均(NMA)模型能有效描述工业过程的动态特性,是一种典型的动态软测量模型.而受限于模型复杂度,NMA模型的输入时序边界相对较窄,难以适应带有大滞后或强测量噪声的动态工业过程.针对该问题,本文将NMA模型与结构简单、输入时序边界宽的FIR滤波器相结合,构造一种非线性、强抗干扰的软测量建模策略.并设计层白化结构来避免二者间的参数耦合现象,采用Adam算法进行同步优化,提高模型的预测精度及训练效率.最后,利用数值仿真和硫回收过程建模实验,验证所提模型的预测精度以及模型设计的合理性.

FIR数字滤波器综合实验设计

把Matlab软件与CCS 5.5软件相结合,完成FIR数字滤波器综合实验设计.借助Matlab软件中的FIR数字滤波器设计函数,求得FIR数字滤波器的单位脉冲响应h(n).通过h(n)得到FIR数字滤波器的直接型网络结构,借助Matlab函数tf2sos,求得FIR数字滤波器的级联型网络结构的系数矩阵和增益,得到FIR数字滤波器的级联型网络结构.提出了实现FIR数字滤波的线性卷积计算方法.根据FIR低通或高通滤波器的截止频率ωc,设计了输入序列x(n).借助CCS 5.5软件,设计实现FIR数字滤波器的直接型网络和级联型网络滤波的C语言程序,很好地完成对输入序列x(n)的滤波.仿真实验结果表明,借助Matlab软件和CCS 5.5软件能够较好地完成FIR数字滤波综合实验设计.

基于一种新的三模集的低通FIR数字滤波器设计

本文对低通有限脉冲响应(FIR)数字滤波器的设计进行了研究;在对常用三模集和传统的具有脉冲响应系数的FIR数字滤波器分析的基础上,提出将一种新的三模集应用于低通FIR数字滤波器设计的新方法。该FIR滤波器由多个乘法-累加器单元构成,实现正向转换器、并行算术通道和逆向转换器的功能。正向转换器将一个二进制数编码成一个关于模集的余数表示的数,每个算术通道对模集的每个模进行模乘和累加,逆向转换器将一个余数表示的数解码为其等效的二进制数,算术通道以完全并行的架构工作,从而实现轻量化的计算和简单的结构;最后的仿真实验结果不仅验证了本文提出的设计方法的有效性,而且相比于传统的单向转换设计,本文提出的设计方法有更小的滤波器系数偏差和更好的频率响应等波纹特性。

基于时间模式信号处理的三阶FIR滤波器实现

文中提出了一种基于时间模式信号处理电路的三阶低通有限脉冲响应(FIR)滤波器的实现。滤波器拓扑由一组新颖的构建块组成,这些构建块在时间模式下执行必要的功能,包括z-1运算、时间加法和时间乘法。设计的时域三阶FIR滤波器的输出与采样频率同步,且该滤波器的拓扑结构是模块化的,因此只需增加延迟和乘法器的数量就可以创建高阶滤波器。滤波器是在28 nm三星全耗尽绝缘体上硅FD-SOI工艺中设计的,电源电压为1 V,采样频率为5 MHz,仿真结果验证了理论分析的正确性,FIR滤波器在50 kHz的输入频率下实现了38.6 dB的信噪加失真比(SNDR),功耗约为200μW。

基于SG FIR Filter的设计方法与分析

基于Xilinx System Generator for DSP工具,在现场可编程逻辑门阵列(FPGA)硬件平台上为了研究FIR滤波器的设计及实现技巧,给出了一个18阶的FIR数字低通滤波器滤波的实验,从滤波器的滤波效果和资源利用率等方面进行了分析,获得了针对不同型号的FPGA芯片和在不同硬件资源环境下,如何选择最优的设计实践方法的结果,得出了使用已封装好的Ipcore来实现所设计的滤波器,不但简单方便,可以减少系统的开发时间,又能有效的利用硬件资源,为最佳选择的结论。

多策略离散人工蜂群算法设计FIR低通数字滤波器

针对人工蜂群(Artificial Bee Colony,ABC)算法在解决复杂问题表现出来精度不高以及收敛速度较慢的不足,提出了一种融合折射学习和Lévy飞行的多策略离散人工蜂群算法(Discrete Artificial Bee Colony Fusing Refraction Learning and Lévy flight,DABC-RL),用于设计有限长脉冲响应(Finite Impulse Response,FIR)低通数字滤波器,以期进一步提高其滤波性能。在DABC-RL算法中,一方面,Lévy飞行策略用于增强ABC算法的局部搜索能力,折射学习用于增强ABC算法的全局搜索能力;另一方面,通过设计合适的离散编码方案对DABC-RL算法中的候选解进行离散化,使其适合于设计FIR低通数字滤波器。为了测试所提的DABC-RL算法设计的FIR低通数字滤波器的性能,选取由ABC算法、基于折射学习的refrPSO算法所设计的FIR低通数字滤波器作为对比算法。实验结果表明,相比其他算法,DABC-RL算法所设计的FIR低通数字滤波器的性能最好,且获得了最快的收敛精度和收敛速度。

A digital energy spectroscopy based on FIR filter

We designed a universal digital energy spectroscopy based on online digital signal processing. A prototype system was built and tested. Signals from radiation detectors were processed via a digital filter whose coefficients could be modified without changing the hardware. The paper introduces the hardware design of the digital energy spectroscopy system as well as the full set of software consisting of the selection of the coefficients of the finite impulse response (FIR) filter and the coding in the field-programmable gate array (FPGA). The system was tested with the high purity germanium (HPGe) detector. The results showed that this prototype can achieve an energy resolution close to that of a traditional multi-channel analyzer (MCA) with a much higher counting rate.

Small-Space Microphone Array Fractional Delay Algorithm Based on FIR Filter for Cochlear Implant

Directional speech enhancement of signals from microphone arrays is an effective way to improve speech recognition for cochlear implant users.The strict implant size limitation results in a short distance between microphones.The fractional delay problem due to the short distance between microphones is solved by a maximal flat (Maxflat) finite impulse response (FIR) filter,using the Maxflat error criteria at a low frequency containing most of the speech information and energy.The fractional Maxflat FIR filter approximates the ideal digital fractional filter at the magnitude response,phase response,and phase delay characteristics,and is also very low order.The results demonstrate that the Maxflat FIR filter accurately and effectively solves the fractional digital delay and is very suitable for real-time speech processing in practical cochlear implant products.

海洋重力数据处理中的正反FIR滤波算法

数字滤波器是影响海洋重力数据处理成果质量的关键技术之一。该文提出了一种实时正反有限冲击响应(FIR)滤波算法,推导了具有线性相位正反FIR滤波器表达式并设计了实时滤波方案:该算法设计出的滤波器在所有的采样频谱内都满足严格意义上的线性相频特性;基于该算法设计的低通滤波器的阻带衰减大,有利于抑制海洋重力数据中的高频噪声。船载重力试验结果表明,在海洋重力数据处理中上述正反FIR滤波器的滤波器实时性好,滤波效果与事后正反FIR滤波器相当,优于单正向FIR滤波效果。

Neural Network Algorithm for Designing FIR Filters Utilizing Frequency-Response Masking Technique

This paper presents a new joint optimization method for the design of sharp linear-phase finite-impulse response (FIR) digital filters which are synthesized by using basic and multistage frequency-response-masking(FRM) techniques.The method is based on a batch back-propagation neural network algorithm with a variable learning rate mode.We propose the following two-step optimization technique in order to reduce the complexity.At the first step,an initial FRM filter is designed by alternately optimizing the subfilters.At the second step,this solution is then used as a start-up solution to further optimization.The further optimization problem is highly nonlinear with respect to the coefficients of all the subfilters. Therefore,it is decomposed into several linear neural network optimization problems.Some examples from the literature are given,and the results show that the proposed algorithm can design better FRM filters than several existing methods.

Forward/backward prediction solution for adaptive noisy FIR filtering

An important and hard problem in signal processing is the estimation of parameters in the presence of observation noise. In this paper, adaptive finite impulse response (FIR) filtering with noisy input-output data is considered and two developed bias compensation least squares (BCLS) methods are proposed. By introducing two auxiliary estimators, the forward output predictor and the backward output predictor are constructed respectively. By exploiting the statistical properties of the cross-correlation function between the least squares (LS) error and the forward/backward prediction error, the estimate of the input noise variance is obtained; the effect of the bias can thereafter be removed. Simulation results are presented to illustrate the good performances of the proposed algorithms.

Optimal design study of high order FIR digital filters based on neural network algorithm

An optimal design approach of high order FIR digital filter is developed based on the algorithm of neural networks with cosine basis function . The main idea is to minimize the sum of the square errors between the amplitude response of the desired FIR filter and that of the designed by training the weights of neural networks, then obtains the impulse response of FIR digital filter . The convergence theorem of the neural networks algorithm is presented and proved, and the optimal design method is introduced by designing four kinds of FIR digital filters , i.e., low-pass, high-pass, bandpass , and band-stop FIR digital filter. The results of the amplitude responses show that attenuation in stop-bands is more than 60 dB with no ripple and pulse existing in pass-bands, and cutoff frequency of passband and stop-band is easily controlled precisely . The presented optimal design approach of high order FIR digital filter is significantly effective.