A critical review of the most popular types of neuro control

In this review article, the most popular types of neural network control systems are briefly introduced and their main features are reviewed. Neuro control systems are defined as control systems in which at least one artificial neural network (ANN) is directly involved in generating the control command. Initially, neural networks were mostly used to model system dynamics inversely to produce a control command which pushes the system towards a desired or reference value of the output (1989). At the next stage, neural networks were trained to track a reference model, and ANN model reference control appeared (1990). In that method, ANNs were used to extend the application of adaptive reference model control, which was a well‐known control technique. This attitude towards the extension of the application of well‐known control methods using ANNs was followed by the development of ANN model‐predictive (1991), ANN sliding mode (1994) and ANN feedback linearization (1995) techniques. As the first category of neuro controllers, inverse dynamics ANN controllers were frequently used to form a control system together with other controllers, but this attitude faded as other types of ANN control systems were developed. However, recently, this approach has been revived. In the last decade, control system designers started to use ANNs to compensate/cancel undesired or uncertain parts of systems' dynamics to facilitate the use of well‐known conventional control systems. The resultant control system usually includes two or three controllers. In this paper, applications of different ANN control systems are also addressed. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Analysis for scattering of conductive objects covered with anisotropic magnetized plasma by trapezoidal recursive convolution finite‐difference time‐domain method

The finite‐difference time‐domain method (FDTD) is extended to three‐dimensional (3D) anisotropic magnetized plasma based on the trapezoidal recursive convolution (TRC) technology. The TRC technique requires single convolution integral in the formulation as in the recursive convolution (RC) method, while maintaining the accuracy comparable to the piecewise linear recursive convolution (PLRC) method with two convolution integrals. In this article, the numerical results indicate that the TRC‐FDTD method not only improves accuracy over the RC‐FDTD with the same computational efficiency but also spends less computational time than the PLRC‐FDTD based on the same accuracy. The 3D TRC‐FDTD formula is provided and the bistatic radar scattering sections of conductive targets covered with anisotropic magnetized plasma are calculated. The results show that magnetized plasma cover layer can greatly reduce echo energy of radar targets, and the anisotropic magnetized plasma cover has better absorption effect than nonmagnetized. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.     

FDTD modeling of matched impedance terminating a microstrip line

An efficient matched‐impedance scheme for the finite‐difference time‐domain (FDTD) analysis of microstrip circuits is presented. In conventional extended FDTD schemes, the resistive load is introduced as a thin‐line model or is uniformly assigned into a number of cells. The assigning scheme does not agree with the electromagnetic distribution in the microstrip line, and thus causes some reflection errors. The proposed scheme uses the effective impedance of the microstrip line as the value of matched resistive load and assigns it into the resistive‐load mesh region in a proper proportion in order to reduce the reflection errors. The results of the numerical examples show that the reflections can be significantly reduced by this novel scheme. © 2005 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2005.     

NFDTD concept

This paper combines artificial neural network (ANN) technique with the finite difference time domain (FDTD) technique. A detailed illustration of the concept, in this paper, uses a 3-8-1 feedforward artificial neural network (FF-ANN) for approximating the Z-component of the electric field in a rectangular waveguide in TM mode. The FDTD equation (i.e., the two-dimensional (2-D) wave equation in discrete form) is embedded into the cost function of the ANN. Results of implementing this technique in a one-dimensional (1-D) transmission line resonator are also provided with 4-10-1 FF-ANN. The result of the leap-frog algorithm implementation, for this 1-D problem using a (3-6-1) /spl times/ (3-6-1) hybrid FF-ANN, is also provided. The neural-finite difference time domain (NFDTD) results are compared with those of the traditional FDTD.     

A novel hybrid algorithm based on FDTD and WCS‐FDTD methods

In this article, a hybrid algorithm based on traditional finite‐difference time‐domain (FDTD) and weakly conditionally stable finite‐difference time‐domain (WCS‐FDTD) algorithm is proposed. In this algorithm, the calculation domain is divided into fine‐grid region and coarse‐grid region. The traditional FDTD method is used to calculate the field value in the coarse‐grid region, while the WCS‐FDTD method is used in the fine‐grid region. The spatial interpolation scheme is applied to the interface of the coarse grid region and fine grid region to insure the stability and precision of the presented hybrid algorithm. As a result, a relatively large time step size, which is only determined by the spatial cell sizes in the coarse grid region, is applied to the entire calculation domain. This scheme yields a significant reduction both of computation time and memory requirement in comparison with the conventional FDTD method and WCS‐FDTD method, which are validated by using numerical results.     

Rotationally symmetric FDTD for wideband performance prediction of TM01 DR filters

The generalized perfectly matched layer (GPML) coupled with rotationally symmetric (RS)‐FDTD method has been utilized to extract the S‐parameters for several probe‐coupled TM₀₁ dielectric resonator (DR) filters to directly obtain the theoretical wideband spurious performance. The computationally efficient (RS)‐FDTD method has also been used to obtain accurate filter parameters for TE₀₁ and TM₀₁ dielectric resonators loaded in cylindrical cavities. The RS‐FDTD method combined with digital filtering and the Matrix Pencil technique are used to analyze the resonant frequencies, inter‐resonator coupling, and external Q values. When perturbation theory is used with RS‐FDTD, accurate values of unloaded Q are obtained. © 2002 Wiley Periodicals, Inc. Int J RF and Microwave CAE 12: 259–271, 2002.     

Signal‐noise support vector model of a microwave transistor

In this work, a support vector machines (SVM) model for the small‐signal and noise behaviors of a microwave transistor is presented and compared with its artificial neural network (ANN) model. Convex optimization and generalization properties of SVM are applied to the black‐box modeling of a microwave transistor. It has been shown that SVM has a high potential of accurate and efficient device modeling. This is verified by giving a worked example as compared with ANN which is another commonly used modeling technique. It can be concluded that hereafter SVM modeling is a strongly competitive approach against ANN modeling. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2007.     

网络流量预测方法和实际预测分析

随着网络带宽的迅速增加以及各种网络服务的广泛应用,针对网络流量的建模以及预测日益重要并备受人们关注。为了更好地对网络流量进行建模和预测,文章一方面将现有的一些流量模型分短相关和长相关两类进行总结和分析;另一方面分析了常见的流量预测方法,尤其是神经网络、模糊理论以及小波分析。并在实际测量中,使用FIR神经网络模型对网络流量进行了实际的预测。最后,提出了流量预测在网络安全领域的应用前景和方向。     

Efficient analysis of wireless communication antennas using an accurate [Z] matrix interpolation technique

An accurate impedance matrix interpolation technique based on the surface integral equation (SIE) is presented for the analysis of wireless communication antennas over wide frequency bands. The first‐order derivative of the impedance matrix at the internal frequency is considered in the cubic polynomial‐based interpolation scheme, thus the novel impedance matrix interpolation scheme will provide high accuracy and high efficiency over a frequency band. To demonstrate the efficiency and accuracy of the proposed method, numerical results for planar inverted F antennas (PIFA) and a wideband E‐shaped patch antenna are presented. Good agreement among the interpolation results, exact MoM solutions, finite element method (FEM) solutions, and measured data is observed over the bandwidth. Besides, dimensions of the feeding probe are also studied to investigate their effect on the input impedance and radiation patterns. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.     

GPU‐accelerated finite‐difference time‐domain method for dielectric media based on CUDA

The simulation of electromagnetic (EM) waves propagation in the dielectric media is presented using Compute Unified Device Architecture (CUDA) implementation of finite‐difference time‐domain (FDTD) method on graphic processing unit (GPU). The FDTD formulation in the dielectric media is derived in detail, and GPU‐accelerated FDTD method based on CUDA programming model is described in the flowchart. The accuracy and speedup of the presented CUDA‐implemented FDTD method are validated by the numerical simulation of the EM waves propagating into the lossless and lossy dielectric media from the free space on GPU, by comparison with the original FDTD method on CPU. The comparison of the numerical results of CUDA‐implemented FDTD method on GPU and original FDTD method on CPU demonstrates that the CUDA‐implemented FDTD method on GPU can obtain better application speedup performance with reasonable accuracy. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:512–518, 2016.     

Triple‐band metamaterial‐inspired antenna using FDTD technique for WLAN/WiMAX applications

In this article, a triple‐band metamaterial (MTM)‐inspired antenna has been designed and analyzed using finite difference time domain technique (FDTD). The proposed MTM consists of two L‐dumbbell‐shaped unit cells, feed, and partial ground plane. The proposed antenna shows triple‐band characteristics with impedance bandwidths of 10.6, 4.67, and 26.8% centered at 2.4, 3, and 5.7 GHz, respectively. The first two bands are working at zeroth‐order resonating mode and first‐order resonating mode while third is due to series slot and coupling between feed and ground plane. It offers compact nature with total antenna size of 30 × 30 × 1.6 mm³. The proposed triple‐band antenna has been designed and analyzed using FDTD code based on convolutional perfectly matched layer boundary conditions and HFSS as well. The prototype antenna has also been fabricated and tested experimentally to validate the simulation results. The proposed antenna exhibits good radiation characteristics throughout the working bands. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:688–695, 2015.     

Computer simulation of polarization rotation characteristics of graphene

The magnetically biased graphene has the polarization rotation characteristics which is useful to design the polarizer. But this characteristic is difficult to simulate by using the finite‐difference time‐domain (FDTD) method, not only due to the graphene's thin layer which confines the time step size, but also because of graphene's isotropic surface conductivity when it is biased by static magnetic field. To solve this problem, this study presents an anisotropic hybrid implicit‐explicit FDTD method. This method uses auxiliary difference equations to represent graphene's conductivity, and removes the confinement of graphene's thickness on time step size by using hybrid implicit‐explicit technique. So, compared with FDTD method, the presented method can save a large number of computational time, which are validated by numerical examples.     

Web服务器区域访问流量预测模型设计

Web服务器上的日志文件记录了用户访问的许多有用的信息,分析和以它建立相应的预测模型,预测区域用户将来的访问行为,对提高Web服务器管理和服务质量,无疑是十分有价值的;Neuro-Fuzzy方法是将神经网络和模糊逻辑有机的结合,用于解决复杂的非线性问题;用它来进行Web服务器区域流量预测,是一种新的思路和方法。文章主要介绍了模型构造的基本思想、结构、算法,也介绍进化式聚类方法和预测过程;同时,给出了实验数据及分析。     

Applications of anisotropic one‐step leapfrog HIE‐FDTD method in microwave circuit and antenna

To verify the effect of artificial anisotropy parameters in one‐step leapfrog hybrid implicit‐explicit finite‐difference time‐domain (FDTD) method, we calculated several microwave components with different characteristics. Introduced auxiliary field variable can reduce the program difficulty and improve the computational efficiency without additional computational time and memory cost. Analyses of the numerical results are proved that the calculation time is reduced to about one‐sixth compared to the traditional FDTD method for the same example simulated. The memory cost and relative error are remained at a good level. The numerical experiments for microwave circuit and antenna have been well demonstrated the method available.     

An impedance and power flow measurement system suitable for on‐wafer microwave device large‐signal characterization

A reflection based and thru‐less de‐embedding technique for impedance and absolute power flow measurements suitable for on‐wafer large‐signal characterization of microwave transistors is proposed. The developed system was tested for both 50 Ω and non‐50 Ω terminated passive and active devices and the results obtained are compared with those obtained with commercial instruments. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.     

Implementation of convolutional perfectly matched layer for three‐dimensional hybrid implicit‐explicit finite‐difference time‐domain method

The hybrid implicit‐explicit (HIE) finite‐difference time‐domain (FDTD) method with the convolutional perfectly matched layer (CPML) is extended to a full three‐dimensional scheme in this article. To demonstrate the application of the CPML better, the entire derivation process is presented, in which the fine scale structure is changed from y‐direction to z‐direction of the propagation innovatively. The numerical examples are adopted to verify the efficiency and accuracy of the proposed method. Numerical results show that the HIE‐FDTD with CPML truncation has the similar relative reflection error with the FDTD with CPML method, but it is much better than the methods with Mur absorbing boundary. Although Courant‐Friedrich‐Levy number climbs to 8, the maximum relative error of the proposed HIE‐CPML remains more below than ?71 dB, and CPU time is nearly 72.1% less than the FDTD‐CPML. As an example, a low‐pass filter is simulated by using the FDTD‐CPML and HIE‐CPML methods. The curves obtained are highly fitted between two methods; the maximum errors are lower than ?79 dB. Furthermore, the CPU time saved much more, accounting for only 26.8% of the FDTD‐CPML method while the same example simulated.     

基于GPU的FDTD麦克斯韦方程快速求解

采用图形处理器(GPU)为主计算核心,应用时域有限差分法(FDTD)实现电磁学中麦克斯韦方程组的快速求解。通过对FDTD求解麦克斯韦旋度方程的直接时间域的分析,给出FDTD的仿真算法。根据GPU能高效地提高FDTD的仿真速度,解决FDTD仿真算法中的计算量庞大问题。利用GPU在FDTD计算中的处理能力,实现了更长的脉冲持续时间和庞大的模型求解与仿真,在适当的时间内完成了超大量的仿真计算。根据在CPU和FDTD上的实际计算结果表明,基于GPU的FDTD仿真算法具有高精度和高效率等特点。     

蝶形天线的计算机仿真设计

蝶形天线是在脉冲型探地雷达中广泛采用的一种宽带天线。本文采用时域有限差分算法(FDTD)结合PML吸收边界条件分析了蝶形天线在高斯脉冲激励下的时域特性,通过傅立叶变换,计算出天线的方向图和在不同频率下的输入阻抗,结果表明FDTD算法用于分析蝶形天线是有效的。     

A study of microwave imaging for a metallic cylinder

This article presents the studies of time‐domain inverse scattering for a metallic cylinder which based on the finite‐difference time‐domain (FDTD) method and the dynamic differential evolution (DDE). For this study, the FDTD is used for the analysis of the forward scattering part, while for the DDE is applied for the reconstruction of the two‐dimensional metallic cylinder. For the forward scattering, the FDTD method is used to calculate the scattered E fields. Based on the scattering fields, these inverse scattering problems are transformed into optimization problem. By comparing the simulated scattered fields and the calculated scattered fields, the shape and location of the metallic cylinder are reconstructed. Numerical results demonstrate that, even when the initial guess is far away from the exact one, good reconstruction can be obtained. In addition, the effects of Gaussian noise on the reconstruction results are investigated. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE , 2012.     

ANN‐based modeling of compact impedance‐varying transmission lines with applications to ultra‐wideband Wilkinson power dividers

The modeling of the physical and electrical characteristics of microstrip non‐uniform transmission lines (NTLs) utilizing artificial neural networks (ANNs) is investigated. The fundamental equations and constraints for designing variable impedance transmission lines are first presented. Then, a proof‐of‐concept example of a compact non‐uniform matching transformer and the counterpart modeled version is elaborated for source and load impedances Z_s and Z_l, respectively, at 0.5 GHz. For comparison purposes, weights and biases of the proposed ANN are established with three different training techniques; namely: backpropagation (BP), Quasi‐Newton (QN), and conjugate gradient (CG); at which the ABCD matrix, impedance variations, input port matching (S₁₁), and transmission parameter (S₂₁) are set as benchmarks to examine the validity of the trained model. The concept is then extended to model a NTL ultrawideband (UWB) Wilkinson power divider (WPD) with three resistors for improved isolation. S‐parameters derived from the trained ANN outputs are close to those obtained by the traditional time‐consuming optimization procedure, and show input and output ports matching and isolation of below ?10 dB, and acceptable values of transmission parameters over the 3.1 GHz to 10.6 GHz band. The resulting models outperform traditional optimizations in terms of simulation time and reserved resources with comparable accuracy. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:563–572, 2015.