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.

基于PSO-BP-UKF算法的锂电池SOC估计方法研究

锂电池的荷电状态(SOC)是锂电池质量管理的核心之一。基于有效的SOC估计是确保锂电池安全高效工作的必要条件,提出一种利用粒子群算法(PSO)优化反向传播(BP)神经网络,并将优化后的BP神经网络SOC输出值作为无迹卡尔曼滤波(UKF)观测值的锂电池SOC估计方法。使用来自马里兰大学的FUDS工况电池测试数据,将所提的PSO-BP-UKF算法与GA-BP-UKF算法、BP算法进行对比。结果表明,在25℃环境下,PSO-BP-UKF算法的最大偏差<3.17%,平均误差<6.44%,均方根偏差<0.0025,相比GA-BP-UKF算法和BP方法都有较大幅度的提高,说明所提算法具备有效性与实用性。

基于改进PSO-BP算法的机器人目标位姿识别方法

机器人作业环境复杂,物料分布具有随机性,导致机器人目标位姿的辨识和定位精度低,实时性差,为此提出一种基于改进粒子群算法-BP神经网络(PSO-BP)的机器人目标位姿识别方法。采用改进的中值滤波算法对目标图像预处理,构建多尺度灰度差异算子以及局部图像熵算子,将两者点积运算获取加权局部熵,抑制目标图像中的噪声。通过多视图几何中间帧的关联特征信息,提取机器人目标位姿特征。在BP神经网络训练阶段通过改进的PSO算法优化处理,采用优化后的BP神经网络算法对提取的特征展开训练和识别,最终实现机器人目标位姿识别。实验结果表明,当机器人目标测试样本数量为55个时,所提方法的亮度方差为0.305,当像素识别误差为1.5%时,所提方法获取的机器人目标位姿识别误差为0.11,所提方法能够在像素识别误差下准确识别机器人目标,获取高精度的机器人目标位姿识别结果。

基于指数平滑和PSO-BP混合模型的建筑工程造价指数预测

建筑工程造价指数是进行工程造价管理的重要依据。为了提高建筑工程造价指数预测的准确性,首先,利用HP滤波将造价指数分解为趋势序列和波动序列,然后采用指数平滑模型对趋势造价指数序列进行预测;其次,利用粒子群算法(PSO)优化的BP神经网络对建筑工程造价指数的波动序列进行预测,PSO-BP神经网络模型的输入指标为引起造价指数变化的4种材料价格;最后,叠加二者预测值即为建筑工程造价指数的预测值。实验结果表明:该混合模型对6个月的造价指数预测的平均相对误差为0.55%,取得了很好的效果,为准确预测建筑工程造价指数提供了一定参考。

Lattice structure adaptive IIR notch filter based on least square kurtosis

A new variable step-size algorithm for a second-order lattice form structure adaptive infinite impulse response （IIR） notch filter to detection and estimation frequency of sinusoids in Gaussian noises is proposed. Utilizing least square kurtosis of output signals as a cost function, the new gradient-based algorithm to update frequency of the adaptive IIR notch filter and the new variable step-size algorithm are given. The computer simulation results show that the proposed algorithm has better ability in suppressing colored Gaussian noises and better accuracy in estimating parameters at low SNR than previous algorithms.

A novel algorithm of adaptive IIR lattice notch filter and performance analysis

A novel adaptive algorithm of IIR lattice notch filter realized by all-pass filter is presented. The time-averaged estimation of cross correlation of the present instantaneous input signal and the past output signal is used to update the step-size, leading to a considerably improved convergence rate in a low SNR situation and reduced steady-state bias and MSE. The theoretical expression for steady-state bounds on the step-size is derived, and the influence factors on the stable performance of the algorithm theoretically are analyzed. A normalized power factor is then introduced to control variation of step-size in its steady-state bounds. This technique prevents divergence due to the influence of large power input signal and improves robustness. Numerical experiments are performed to demonstrate superiority of the proposed method.

Notch filter feedback controlled chaos in buck converter

A method of controlling chaos in the voltage-mode buck converter is presented by using an improved notch filter feedback control in this paper. The proposed control part comprises a notch filter and a low-pass filter. The discrepancy between the outputs of the two filters is introduced into the control prototype of the power converter. In this way, the system period-1 solution is kept unchanged. The harmonic balance method is applied to analysing the variation law of the system bifurcation point, and then the stable range of the feedback gain is ascertained. The results of simulation and experiment are also given finally.

Multi-Frequency Interference Detection and Mitigation Using Multiple Adaptive IIR Notch Filter with Lattice Structure

Radio Frequency Interferences (RFI), such as strong Continuous Wave Interferences (CWI), can influence the Quality of Service (QoS) of communications, increasing the Bit Error Rate (BER) and decreasing the Signal-to-Noise Ratio (SNR) in any wireless transmission, including in a Digital Video Broadcasting (DVB-S2) receiver. Therefore, this paper presents an algorithm for detecting and mitigating a Multi-tone Continuous Wave Interference (MCWI) using a Multiple Adaptive Notch Filter (MANF), based on the lattice form structure. The Adaptive Notch Filter (ANF) is constructed using the second-order IIR NF. The approach consists in developing a robust low-complexity algorithm for removing unknown MCWI. The MANF model is a multistage model, with each stage consisting of two ANFs: the adaptive IIR notch filter Hl(z) and the adaptive IIR notch filter HN(z), which can detect and mitigate CWI. In this model, the ANF is used for estimating the Jamming-to-Signal Ratio (JSR) and the frequency of the interference (w(0)) by using an LMS-based algorithm. The depth of the notch is then adjusted based on the estimation of the JSR. In contrast, the ANF HN(z) is used to mitigate the CW interference. Simulation results show that the proposed ANF is an effective method for eliminating/reducing the effects of MCWI, and yields better system performance than full suppression (kN=1) for low JSR values, and mostly the same performance for high JSR values. Moreover, the proposed can detect low and high JSR and track hopping frequency interference and provides better Bit error ratio (BER) performance compared to the case without an IIR notch filter.

Theoretical and experimental study of Chen chaotic system with notch filter feedback control

Since the past two decades, the time delay feedback control method has attracted more and more attention in chaos control studies because of its simplicity and efficiency compared with other chaos control schemes. Recently, it has been proposed to suppress low-dimensional chaos with the notch filter feedback control method, which can be implemented in a laser system. In this work, we have analytically determined the controllable conditions for notch filter feedback controlling of Chen chaotic system in terms of the Hopf bifurcation theory. The conditions for notch filter feedback controlled Chen chaoitc system having a stable limit cycle solution are given. Meanwhile, we also analysed the Hopf bifurcation direction, which is very important for parameter settings in notch filter feedback control applications. Finally, we apply the notch filter feedback control methods to the electronic circuit experiments and numerical simulations based on the theoretical analysis. The controlling results of notch filter feedback control method well prove the feasibility and reliability of the theoretical analysis.

基于PSO的FIR数字滤波器设计

有限冲激响应(FIR)数字滤波器的设计实质是一个多参数优化的问题,而传统的一些优化设计方法,如遗传算法、神经网络法等,存在算法复杂,收敛速度慢,效果不明显等缺点。提出一种改进粒子群优化算法(IMPSO)的FIR数字滤波器设计。该方法首先根据粒子聚合度情况引入变异思想,克服PSO算法容易早熟的毛病,对算法进行改进,然后利用改进的IMPSO搜索滤波器参数的最优解,对FIR滤波器进行优化设计。实例设计FIR数字低通、带通滤波器,仿真结果表明,该方法具有算法简单,收敛速度快,鲁棒性好等优点。

自适应卡尔曼滤波与PSO-GA-BP算法的机器人误差补偿

采用七轴机器人设备夹持激光器的方式对某型号发射筒进行切割开孔加工。在加工过程中,因轨迹精度和绝对定位精度较低,容易对型号产品发射筒产生损伤和误差切割等问题,运用D-H算法建立七轴机器人理想模型,运用正逆运动学数值算法对理想模型进行验证,运用理想模型的理论位姿参数和激光跟踪仪的测量位姿参数基于Sage-Husa自适应卡尔曼滤波求解七轴机器人真实位姿坐标信息,得到理想位姿参数和真实位姿坐标信息的关节误差,然后结合粒子群优化-遗传算法-BP神经网络联合算法对七轴机器人建立误差预测模型,采用七轴机器人理论位姿参数作为输入样本,真实位姿与理论位姿的各关节角度差作为输出样本,通过库卡机器人Workvisual 5.0软件按照模型输出值对七轴机器人的各关节角度值进行补偿。经过仿真实验和加工,各关节误差补偿后的七轴机器人轨迹误差和绝对定位误差减小72%,满足工艺要求。

Performance Analysis of an Inverse Notch Filter and Its Application to <i>F₀</i>Estimation

In this paper, we analyze an inverse notch filter and present its application to F0 (fundamental frequency) estimation. The inverse notch filter is a narrow band pass filter and it has an infinite impulse response. We derive the explicit forms for the impulse response and the sum of squared impulse response. Based on the analysis result, we derive a normalized inverse notch filter whose pass band area is identical to unit. As an application of the normalized inverse notch filter, we propose an F0 estimation method for a musical sound. The F0 estimation method is achieved by connecting the normalized inverse notch filters in parallel. Estimation results show that the proposed F0 estimation method effectively detects F0s for piano sounds in a mid-range.

The Effect of Notch Filter on RFI Suppression

Radio Frequency Interference (RFI) suppression is an important technique in the ultra-wideband synthetic aperture radar (UWB SAR). In this paper, we mainly analyze the performance of a notch filter for RFI sup-pression. The theoretical output from notch filter is presented based on RFI signal’s narrowband property. The research conclusion shows that the notch filter has significant effect on sidelobes of the system response, which might be considered to be false targets, however it has little effect on the resolution of the system re-sponse. The theoretical result is verified by simulation and experimental data processing both in one dimen-sion (range dimension) and in two dimensions (range and azimuth dimension).

BER of OFDM System with Multiple NBI Rejection Cascade Complex Coefficient Adaptive IIR Notch Filter

In this paper, rejection of multiple narrowband interferers in a binary phase shift keying modulated orthogonal frequency division multiplexing (BPSK-OFDM) system is investigated. The BPSK-OFDM system in consideration operates in an additive white Gaussian noise (AWGN) channel. A cascade complex coefficient adaptive infinite impulse response (IIR) notch filter with gradient-based algorithm is used to reject the interferers. Bit error ratio (BER) performance of the system is studied and a general closed-form expression is derived assuming negligible steady-state leakage NBI and by estimating the decision variable as Gaussian distributed based on Central Limit Theorem (CLT). Dependence of the BER performance on the notch bandwidth coefficient is demonstrated by the analysis. Extensive simulation results are included to substantiate accuracy of the analysis.

Design of Low Power CMOS LNA with Current-Reused and Notch Filter Topology for DS-UWB Application

This paper presents the design of a low power LNA with second stage that uses a notch filter for DS-UWB application. The LNA employs a current reuse structure to reduce the power consumption and an active second order notch filter to produce band rejection in the 5 - 6 GHz frequency band. The input reflection coefficient S11 and output reflection S22 are both less than –10 dB. The maximum power gain S21 is 15 dB while the maximum rejection ratio is over –10 dB at 4.8 GHz. The minimum noise figure is 5 dB. The input referred third-order intercept point (IIP3) is –7 dBm at 6 GHz. The power consumption is 6.4 mW from a 1-V power supply.

TIME-VARYING AR MODELING AND ADAPTIVE IIR NOTCH FILTER FOR ANTI-JAMMING DSSS RECEIVER

Using Time-Varying AR (TVAR) model and adaptive notch filter is a new method for the non-stationary jammer suppression in Direct Sequence Spread Spectrum (DSSS). The performance of TVAR model for Instantaneous Frequency (IF) estimation will be affected by some factors such as basis functions. Focusing on this problem, the optimal basis function of TVAR model for the IF estimation of the LFM signal is obtained in this paper. Besides the depth and width of notching, the phase properties of notch filter affect the Signal-to-Interference plus-Noise Ratio (SINR) of correlation output to the narrowband jammer suppression in DSSS, in response to the problem the closed solution of correlation output SINR improvement has been derived when a single frequency jammer passes through direct IIR notch filter, and its performance has been compared with those of five coefficient FIR filters. Later, a novel method for LFM jammer suppression based on Fourier basis TVAR model and direct IIR notch filter is proposed. The simulation results show the effectiveness of the proposed method.

改进的PSO-CFIWA算法在FIR设计中的应用

FIR数字滤波器的设计是一个组合优化问题,可以用PSO算法来完成。在原有的PSO-CFWIA算法的基础上提出一种改进的PSO-CFWIA算法,该算法关注迭代过程中的粒子位置和当前最优位置的距离,改进后的算法在性能方面稍优于原有算法。

基于PSO的级联马赫-曾德尔型光滤波器优化设计

首次应用连续和离散版本的粒子群优化算法(PSO),实现级联马赫-曾德尔干涉仪(MZI)型光滤波器中关键结构参数(耦合角和相移因子)对理想系数的逼近,完成光滤波器的优化设计.结果表明:三级级联MZI型滤波器输出响应与理想响应之间的误差控制在10-5量级内;同时与遗传算法(GA)设计方案相比,PSO方案具备计算时间少、逼近适应度好、滤波消光比高的特点.

基于PSO算法的大时滞过程双自由度内模控制器设计

借助双控制器设计技术和粒子群优化(PSO)算法,提出了一种基于PSO算法的双自由度内模控制方法,即PSO-TDF-IMC,并用于对大时滞工业过程的控制。该方法的基本思想是:以时间乘误差绝对值积分(ITAE)为目标函数,运用PSO算法,优化整定IMC滤波器时间常数。MATLAB仿真结果表明,PSO-TDF-IMC具有算法简单、搜索速度快、效率高等优点,可明显提高双自由度内模控制系统的设定值跟踪性能和鲁棒性能。