Algorithm for detecting frequencies in multi‐sine signals by inductive generation

Prony's method is an approximation approach to decomposing a function into sum of exponents and thus is applicable to unknown frequencies estimation of signals. The concrete algorithms for estimating pure sine wave, triple tone, and quadruple tone have already been derived and presented. This paper aims at deriving the estimating algorithm for multi‐sine signals which consist of unknown sine waves. The new method of generating an algebraic algorithm for detecting unknown frequencies in the signals is derived by mathematical induction. The crux of the generation is dependent on the integer matrices induction. A handy method for generating the matrices is shown as well. Algorithms for the triple tone, quadruple tone, and the higher‐order tone are generated and verified. As a result, they are shown to be identical to the ordinary algorithms. Subjects on the application of the induced algorithm to practical frequency detection are discussed. The algorithm has both instantaneity in the time domain and higher resolution in the frequency domain, that is, the signal analysis by the algorithm can be performed without constraint of the uncertainty principle. An iterative solution for algebraic equation is dominant for calculation in the algorithm. Techniques for detecting frequencies in a multi‐sine of unknown order are also discussed. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 160(3): 27– 38, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20404     

Development of a computed tomography algorithm for ion temperature measurement

A new algorithm for 2D ion temperature measurement was developed by including Gaussian fitting of Doppler broadened spectral lines in tomography reconstruction. A modified Bessel function model and squared cosine function model were used to satisfy both the annular boundary conditions in space and the Gaussian profile of spectral lines in wavelength. This method was found much more robust against projection signal errors than the conventional Gaussian‐fitting method at each wavelength. © 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 142(4): 1–8, 2003; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10114     

基于FastICA-BAS-MCKD的滚动轴承复合故障特征提取方法

针对强背景噪声下轴承复合故障特征难以分离提取的问题,提出了一种基于快速独立成分分析-天牛须-最大相关峭度 解卷积算法(FastICA-BAS-MCKD)的滚动轴承复合故障特征提取方法。 首先,引入 FastICA 对滚动轴承多通道故障信号进行盲 源分离;其次,利用 BAS 算法同步优化 MCKD 算法的解卷积周期 T、滤波器长度 L 和移位数 M,构建基于 BAS-MCKD 的滚动轴 承振动信号自适应分析方法;然后,应用 BAS-MCKD 方法处理分离后的信号,实现分离信号的降噪和特征增强;最后,应用希尔 伯特解调方法对 MCKD 处理后的信号进行包络谱分析,实现滚动轴承不同类型故障的识别。 仿真和实测信号的分析结果表 明,所提方法能清晰地从复合故障信号中提取出单一故障特征频率,为滚动轴承复合故障特征提取提供了一种有效的解决 方案。     

Feature extraction by supervised independent component analysis based on category information

Independent component analysis (ICA) is a technique of transforming observation signals into their unknown independent components; hence, ICA has often been applied to blind signal separation problems. In this application, it is expected that the obtained independent components extract essential information of independent signal sources from input data in an unsupervised fashion. Based on such characteristics, ICA is currently utilized as a feature extraction method for images and sounds for recognition purposes. However, since ICA is an unsupervised learning, the obtained independent components are not always useful in recognition. To overcome this problem, we propose a supervised approach to ICA using category information. The proposed method is implemented in a conventional three‐layered neural network, but its objective function to be minimized is defined not only for the output layer but also for the hidden layer. The objective function consists of the following two terms: one evaluates the kurtosis of hidden unit outputs and the other evaluates the error between output signals and their teacher signals. The experiments are performed using several standard datasets to evaluate performance of the proposed algorithm. It is confirmed that a higher recognition accuracy is attained by the proposed method as compared with a conventional ICA algorithm. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 161(2): 25–32, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20522     

Particle Swarm Optimization Based Global Descent Method

This letter proposes a new global descent method based on not only the concept of a conventional descent method in mathematical programming but also the concept of search direction in particle swarm optimization (PSO) in metaheuristics. The proposed method, called particle swarm optimization based global descent method (PSOGDM), consists of two main procedures; (i) determination of search direction and (ii) global optimization for given search direction. Although the search direction that has three parameters is decided based on the concept of PSO, the proposed PSOGDM is a single-point search different from PSO. Global optimization for a given search direction is performed by PSO. The search capability of the proposed PSOGDM is examined based on the results of numerical experiments using five typical benchmark problems. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Blind deconvolution by a Newton method on the non‐unitary hypersphere

Blind deconvolution is an inverse filtering technique that has received increasing attention from academia as well as industry because of its theoretical implications and practical applications, such as in speech dereverberation, nondestructive testing and seismic exploration. An effective blind deconvolution technique is known as ‘Bussgang’, which relies on the iterative Bayesian estimation of the source sequence. Automatic gain control in blind deconvolution keeps constant the energy of the inverse filter impulse response and controls the magnitude of the estimated source sequence. The aim of the present paper is to introduce a class of Newton‐type algorithms to optimize the Bussgang cost function on the inverse‐filter parameter space whose geometrical structure is induced by the automatic‐gain‐control constraint. As the parameter space is a differentiable manifold, the Newton‐like optimization method is formulated in terms of differential geometrical concepts. The present paper also discusses convergence issues related to the introduced Newton‐type optimization algorithms and illustrates their performance on a comparative basis.Copyright © 2012 John Wiley & Sons, Ltd.     

Improvement of a Fourier coefficient estimation method using an adaptive algorithm and its performance analysis

There are many applications where it is necessary to estimate accurately the amplitude and phase of signals when the information regarding the frequencies is obtained in advance. This paper presents a new algorithm for estimating more accurately Fourier coefficients of a signal contaminated by additive noise where sinusoidal frequencies of interest are not distributed uniformly. In the proposed method, Fourier coefficients are adaptive parameters. It uses averaged gradient signals and has almost the same acquisition time as the conventional LMS algorithm with more accurate estimation. The performance analysis of the proposed method is presented and its validity and limits are verified under various conditions by computer simulations. It is shown that the proposed method has especially better performance than the LMS algorithm when both the number of frequencies and the step size parameter, µ, are large. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 149(1): 52–60, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10362     

Adaptive finite element method for shape modification in optimization of electric machines

A method for the modification of finite element meshes based on adaptive meshing for optimization of electric machines is proposed. In the optimization of the machine, the proposed method generates the mesh for the new shape from the previous mesh with minor modification. The locations of the nodes for the new shape are decided by solving a Laplacian equation whose unknowns are the displacements of the nodes. The advantages are illustrated by application to the shape optimization of an IPM motor. © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 168(1): 21–28, 2009; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20773     

Convergence analysis of blind image deconvolution via dispersion minimization

A new non‐linear adaptive filter called blind image deconvolution via dispersion minimization has recently been proposed for restoring noisy blurred images blindly. This is essentially a two‐dimensional version of the constant modulus algorithm that is well known in the field of blind equalization. The two‐dimensional extension has been shown capable of reconstructing noisy blurred images using partial a priori information about the true image and the point spread function in a variety of situations by means of simulations. This paper analyses the behaviour of the algorithm by investigating the static properties of the cost function and the dynamic convergence of the parameter estimates. The theoretical results are supported with computer simulations. Copyright © 2006 John Wiley & Sons, Ltd.     

Numerical computation for solving algebraic Riccati equations of weakly coupled systems

In this paper, an algorithm for solving the algebraic Riccati equation (ARE) that has an indefinite sign quadratic term related to weakly coupled large‐scale systems is investigated. A novel contribution is that a new iterative algorithm is derived by combining Newton's method and the fixed point algorithm. As a result, for sufficiently small ε, we can obtain an ARE solution with a quadratic convergence rate. Moreover, it is possible to calculate the ARE solution for the same dimension of each subsystem. As another important feature, an algorithm for solving the filter ARE is also discussed. Finally, in order to demonstrate the efficiency of the proposed algorithm, a numerical example is given. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 160(1): 39–48, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20370     

基于最小熵解卷积的轨面缺陷漏磁信号处理

钢轨表面缺陷的漏磁检测会受到巡检速度等因素的影响,导致背景噪声增大,检测灵敏度降低。为了增强缺陷信号特征,提高漏磁信号的信噪比,提出了一种基于最小熵解卷积的漏磁信号处理方法。通过目标函数法,计算得到最优的逆滤波器参数,对采集到的漏磁信号进行滤波处理。为衡量最小熵解卷积算法滤波效果,将处理得到的缺陷信号和背景噪声信号的峰峰值与小波变换法和中值滤波法进行对比。实验结果表明,最小熵解卷积算法对缺陷信号起到了明显的增强作用,且其效果优于小波变换和中值滤波。     

Determination of the step response function of a dielectric in the presence of noise

In the time domain characterization of dielectrics a fundamental measure is the dielectric response function /spl Phi/(t). This function permits the relaxation time and the complex permittivity of the dielectric under test to be determined, allowing the complete characterization of the dielectric properties. To calculate the /spl Phi/(t) function a time domain deconvolution algorithm (TDD), developed in a previous work, is employed. In this paper a new technique to enhance the calculation of the /spl Phi/(t) function in the time domain, is presented, avoiding the instability problems inherent to the TDD algorithm. The method consists in the use of appropriate digital lowpass filter in several stages of the time domain deconvolution algorithm to calculate the /spl Phi/(t) function. This procedure provides an enhanced precision for /spl Phi/(t) even for very short times (/spl ap/ 10 ps for the time domain reflectometry system used).     

Distributed fusion white noise deconvolution estimators

The white noise deconvolution or input white noise estimation problem has important applications in oil seismic exploration, communication and signal processing. By combining the Kalman filtering method with the modern time series analysis method, based on the autoregressive moving average (ARMA) innovation model, new distributed fusion white noise deconvolution estimators are presented by weighting local input white noise estimators for general multisensor systems with different local dynamic models and correlated noises. The new estimators can handle input white noise fused filtering, prediction and smoothing problems, and are applicable to systems with colored measurement noise. Their accuracy is higher than that of local white noise deconvolution estimators. To compute the optimal weights, the new formula for local estimation error cross-covariances is given. A Monte Carlo simulation for the system with Bernoulli-Gaussian input white noise shows their effectiveness and performance.     

高分辨THz-TDS采集传输的嵌入式设计与优化

为了满足太赫兹高分辨检测及实时处理需求,利用光电导天线产生和探测太赫兹时域光谱信号,基于现场可编程门阵列(field programmable gate array, FPGA)实现太赫兹时域光谱的采集、维纳滤波反卷积处理、传输和上位机显示等功能。将采集到的太赫兹时域光谱数据进行维纳滤波反卷积处理,实现还原太赫兹信号、提高时间分辨率以及降噪的效果,将数据由以太网传输的方式传输到上位机进行实时显示,针对实际检测中太赫兹信号反卷积后脉宽较宽,提出在维纳滤波反卷积算法中引入与频率相关的函数对算法进行优化,使信号的脉宽变窄,提高检测精度。优化的维纳滤波反卷积算法处理结果相比于原始算法信噪比增加7 dB,脉宽降低0.2 ps,实现更高的检测分辨能力,算法在FPGA中实现,精度误差小于0.7%,处理效率提升14.29倍,并且减少后期上位机处理时间。     

Evaluation of instantaneous power by the aspectum in the theory of the natural observation method

In this paper signal processing by aspectum was applied to actual waveforms for the first time. Aspectum is the quantity to estimate the instantaneous power on the theory of natural observation method, which was proposed by Iijima. It can quantitatively evaluate the instantaneous power of signals. To begin with, characteristics of the aspectum were clearly shown by applying it to known model signals. The result of analysis of observed electromagnetic field signals radiated by lightning discharge was shown as a sample applying aspectum to actual waveforms. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 153(1): 25–33, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20130     

Optimal placement of SVRs considering multiple loads

This paper presents a new approach to the optimal placement of a step voltage regulator (SVR) taking into consideration the installation of distributed generators (DG) based on a genetic algorithm (GA). In this case, it is necessary to solve problems such as the upper and lower limits for the voltage at each node and line capacity. In addition, given that the load and output of a distributed generator change, it is important to solve more than one of these problems. In order to solve these problems, the conventional genetic algorithm was improved and the proposed method was applied to the complex operating conditions of a distribution power system. © 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 182(1): 39–47, 2013; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21297     

注入电流式磁声成像平面模型的逆问题研究

注入电流式磁声成像是电阻抗成像和超声成像相结合的一种新型成像技术,具有电阻抗成像的高对比度和超声成像高分辨率的优势,是一种有望获得高质量图像的生物电阻抗成像技术,在生物医学成像领域具有广阔的应用前景。作为一种新型成像技术,目前在电导率的重建方面还没有形成完整的体系。针对二维平面模型,提出一种由声场信号准确重建被测样品电流密度的方法。首先采用维纳滤波反卷积方法由超声换能器测量的声场信号重建被测样品原始声场p(r,t),接着利用时间反演法获取声源分布0??(J×B),然后考虑到二维平面模型只有电流密度的两个分量,结合电流连续性定理,从而重建电流密度的两个分量xJ、yJ,最后设计并搭建注入式磁声成像实验平台,利用生物组织进行实验,最终得到猪肉组织的电导率图像,重建结果证明了重建方法的可行性。     

Novel design for non‐latency wireless binaural hearing aids

Binaural hearing aids consist of two hearing devices, one for each ear. A new concept of binaural hearing aids is proposed, in which only the master hearing aid contains a Bluetooth chip for receiving stereo audio signals from an external device, and the signal in one channel is sent to the slave hearing aid from the master by a 2.4‐GHz Gaussian frequency‐shift keying (GFSK) RF transmission method to create the binaural hearing effect. However, a problem arises in regard to the processing necessary for the signal transmission and reception in the two hearing aids, which creates a time delay that causes the precedence effect. Therefore, an audio delay processing algorithm has been designed in the master hearing aid to synchronize with the sound output of the slave hearing aid. Experimental results show that the time difference between the two hearing aids is about 8 µs, which is effective for avoiding the precedence effect. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Cutting plane methods for Lagrangian relaxation‐based unit commitment algorithm

In this paper, we study cutting plane methods for a Lagrangian relaxation‐based unit commitment algorithm. In the algorithm, nondifferentiable optimization methods can be applied to optimize the dual function, and a subgradient method which needs parameter tuning and has some drawbacks such as computational inefficiency and oscillating behavior is commonly used. The cutting plane method and the central cutting plane method are applied to the algorithm and implemented using reoptimization techniques. A numerical example shows that both methods are accelerated by the reoptimization techniques and have good convergence without parameter tuning. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 141(3): 17–29, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10066     

基于EMD的电弧反射电缆故障测距脉冲信号提取方法

电弧反射法(ARM)电缆故障测距脉冲信号受故障电弧电压的干扰,故障反射脉冲不易识别,无法满足故障定位要求。分析了干扰产生的原因和受扰脉冲信号的特性,通过经验模态分解(EMD)分析了受扰脉冲信号的时频分布规律。论证了根据受扰脉冲信号特定时段均值特性可以对脉冲信号和干扰进行分离。据此提出基于受扰脉冲信号特定时段均值特性和EMD滤波的ARM脉冲信号提取算法。该方法不需要预定义信号分解层数和基函数,完全由数据驱动实现,因而具有较好的自适应能力。实测数据处理结果验证了算法的有效性。