Noise removal for medical X‐ray images in wavelet domain

Many important problems in engineering and science are well‐modeled by Poisson noise, and the noise of medical X‐ray images is Poisson noise. In this paper, we propose a method for noise removal for degraded medical X‐ray images using improved preprocessing and an improved BayesShrink (IBS) method in the wavelet domain. First, we preprocess the medical X‐ray image. Second, we apply the Daubechies (db) wavelet transform to medical X‐ray images to acquire scaling and wavelet coefficients. Third, we apply the proposed IBS method to process wavelet coefficients. Finally, we compute the inverse wavelet transform for the threshold coefficients. Experimental results show that the proposed method always outperforms traditional methods. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 163(3): 37– 46, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20486     

A new blind source separation method based on fractional lower‐order statistics

We proposed neural network structures related to multilayer feed‐forward networks for performing blind source separation (BSS) based on fractional lower‐order statistics. As alpha stable distribution process has no its second‐ or higher‐order statistics, we modified conventional BSS algorithms so that their capabilities are greatly improved under both Gaussian and lower‐order alpha stable distribution noise environments. We analysed the performances of the new algorithm, including the stability and convergence performance. The analysis is based on the assumption that the additive noise can be modelled as alpha stable process. The simulation experiments and analysis show that the proposed class of networks and algorithms is more robust than second‐order‐statistics‐based algorithm. Copyright © 2006 John Wiley & Sons, Ltd.     

Estimation algorithm for system with non‐Gaussian multiplicative/additive noises based on variational Bayesian inference

This paper considers estimation algorithms for linear and nonlinear systems contaminated by non‐Gaussian multiplicative and additive noises. Based on the variational idea, in order to derive optimal estimation algorithms, we combine the multiplicative noise with states as the joint parameters to estimate. The application of variational Bayesian inference to joint estimation of the state and the multiplicative noise is established. By treating the states as unknown quantities as well as the multiplicative noise, there are now correlations between the states and multiplicative noise in the posterior distribution. There are two main goals in Bayesian learning. The first is approximating the marginal likelihood (PDF of multiplicative noise) to perform model comparison. The second is approximating the posterior distribution over the states (also called a system model), which can then be used for prediction. The two goals constitute the iterative algorithm. The rules for determining the loop is the Kullback‐Leibler divergence between the true distribution of state and a chosen fixed tractable distribution, which is used to approximate the true one. The iterative algorithm is deduced, which is initialized based on the idea of sampling. Meanwhile, the convergence analysis of the proposed iterative algorithm is presented. The numerical simulation results in a comparison between the proposed method and these existing classic algorithms in the context of nonlinear hidden Markov models, state‐space models, and target‐tracking models with non‐Gaussian multiplicative noise demonstrate the superiorities, not only in speed, precision, and computation load but also in the ability to process non‐Gaussian complex noise.     

Adaptive filtering‐based multi‐innovation gradient algorithm for input nonlinear systems with autoregressive noise

In this paper, by means of the adaptive filtering technique and the multi‐innovation identification theory, an adaptive filtering‐based multi‐innovation stochastic gradient identification algorithm is derived for Hammerstein nonlinear systems with colored noise. The new adaptive filtering configuration consists of a noise whitening filter and a parameter estimator. The simulation results show that the proposed algorithm has higher parameter estimation accuracies and faster convergence rates than the multi‐innovation stochastic gradient algorithm for the same innovation length. As the innovation length increases, the filtering‐based multi‐innovation stochastic gradient algorithm gives smaller parameter estimation errors than the recursive least squares algorithm.     

A new adaptive multi‐bias S‐parameter measurement algorithm for transistor characterization

A new adaptive measurement algorithm is described for the control of an automated S‐parameter measurement set‐up used to characterize transistors for non‐linear modelling. The procedure differs from previous algorithms in that is uses both the device DC‐ and S‐parameter data to identify DC bias regions where the device characteristics are changing rapidly. By placing more bias points in these areas and less data points in regions where the device response stays constant, the non‐linear behaviour of the device can be characterized more accurately while keeping the total volume of the experimental data and hence the measurement time to an acceptable level. Experimental results are presented that illustrates the operation of the adaptive algorithm as well as the influence that the selection procedure has on non‐linear modelling results. Copyright © 2005 John Wiley & Sons, Ltd.     

A numerical model for the oscillation frequency,the amplitude and the phase‐noise of MOS‐current‐mode‐logic ring oscillators

This paper presents a new model for the frequency of oscillation, the oscillation amplitude and the phase‐noise of ring oscillators consisting of MOS‐current‐mode‐logic delay cells. The numerical model has been validated through circuit simulations of oscillators designed with a typical 130 nm CMOS technology. A design flow based on the proposed model and on circuit simulations is presented and applied to cells with active loads. The choice of the cell parameters that minimize phase‐noise and power consumption is addressed. Copyright © 2009 John Wiley & Sons, Ltd.     

A new multi‐focus image fusion algorithm based on BEMD and improved local energy

A multi‐focus image fusion method, which is based on bidimensional empirical mode decomposition (BEMD) and improved local energy algorithm, is presented in this paper. First, the source image is decomposed by BEMD. Then maximum criterion combined with weighted average fusion rule based on local energy is applied to bidimensional intrinsic mode function components of the corresponding frequency segment. If the phase of the bidimensional intrinsic mode function coefficients decomposed by BEMD on two source images is the same, the local energy maximum criterion is used in the frequency coefficients of the fused image; else, if the corresponding phase is opposite, bidimensional intrinsic mode function coefficients of the fused image is determined by a weighted average method based on local energy. Finally, the fusion result is obtained by the inverse BEMD transformation on the fusion coefficient. Simulation shows that the proposed algorithm significantly outperforms traditional methods such as the maximum criterion, weighted average, and wavelet fusion rules. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Low‐frequency noise analysis and minimization in Gilbert‐cell‐based mixers for direct‐conversion (zero‐IF) low‐power front‐ends

Low‐frequency (flicker) noise is one of the most important issues in the design of direct‐conversion zero‐IF front‐ends. Within the front‐end building blocks, the direct‐conversion mixer is critical in terms of flicker noise, since it performs the signal down‐conversion to baseband. This paper analyzes the main sources of low‐frequency noise in Gilbert‐cell‐based direct‐conversion mixers, and several issues for minimizing the flicker noise while keeping a good mixer performance in terms of gain, noise figure and power consumption are introduced in a quantitative manner. In order to verify these issues, a CMOS Gilbert‐cell‐based zero‐IF mixer has been fabricated and measured. A flicker noise as low as 10.4 dB is achieved (NF at 10 kHz) with a power consumption of only 2 mA from a 2.7 V power supply. More than 14.6 dB conversion gain and noise figure lower than 9 dB (DSB) are obtained from DC to 2.5 GHz with an LO power of ?10 dBm, which makes this mixer suitable for a multi‐standard low‐power zero‐IF front‐end. Copyright © 2008 John Wiley & Sons, Ltd.     

Steiglitz–McBride adaptive notch filter based on a variable‐step‐size LMS algorithm and its application to active noise control

This paper proposes a new Steiglitz–McBride (SM) adaptive notch filter (SM‐ANF) based on a robust variable‐step‐size least‐mean‐square algorithm and its application to active noise control (ANC). The proposed SM‐ANF not only has fast convergence but also has small misadjustment. The variable‐step‐size algorithm uses the sum of the squared cross correlation between the error signal and the delayed inputs corresponding to the adaptive weights. The cross correlation provides robustness to the broadband signal, which plays the role of noise. The proposed SM‐ANF is computationally simpler than the existing Newton/recursive least‐squares‐type ANF. The frequency response of the new SM‐ANF has a notch depth of about ?25 dB (for each of the three frequencies considered) and has spectral flatness within 5 dB (peak to peak). This robust notch filter algorithm is used as an observation noise canceller for the secondary path estimation of an ANC system based on the SM method. The ANC with proposed SM‐ANF provides not only faster convergence but also an 11‐dB improvement in noise attenuation over the SM‐based ANC without such a SM‐ANF. Copyright © 2015 John Wiley & Sons, Ltd.     

A two‐step scheme for polynomial NARX model identification based on MOEA with prescreening process

Polynomial NARX (nonlinear autoregressive with exogenous) model identification has received considerable attention in last three decades. However, in a high‐order nonlinear system, it is very difficult to obtain the model structure directly even with state‐of‐art algorithms, because the number of candidate monomial terms is huge and increases drastically as the model order increases. Motivated by this fact, in this research, the identification is performed in two steps: firstly a prescreening process is carried out to select a reasonable number of important monomial terms based on two kinds of the importance indices. Then, in the reduced searching space with only the selected important terms, multi‐objective evolutionary algorithm (MOEA) is applied to determine a set of significant terms to be included in the polynomial model with the help of independent validation data. In this way, the whole identification algorithm is implemented efficiently. Numerical simulations are carried out to demonstrate the effectiveness of the proposed identification method. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A new current control strategy based on the internal model principle for a current balancer in single‐phase three‐wire distribution systems

This paper proposes a new current control strategy that is based on the internal model principle for a current balancer in single‐phase three‐wire distribution systems. The proposed current control strategy includes a sinusoidal reference input model to achieve the zero steady‐state error tracking. The appropriate control gains of this control strategy can be systematically determined by using a state‐feedback controller design method via linear matrix inequalities. The basic principle of the proposed control strategy is discussed in detail, and then confirmed by digital computer simulation using the PSIM software. A prototype experimental model is constructed and tested. Experimental results demonstrate that zero steady‐state error tracking is achieved by the proposed control strategy. Also, balanced source currents are obtained on the secondary side of a pole‐mounted distribution transformer while the load conditions are unbalanced. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A new sequential AC–DC power flow algorithm for multi‐terminal HVDC systems

This paper presents a new algorithm based on the sequential method for power flow calculation in integrated multi‐terminal, high‐voltage, direct current (HVDC) systems. Unlike similar studies in the literature, a real equivalent circuit model is considered for under‐load tap changer (ULTC) transformers of the DC converters, for the first time. So, new DC equations are obtained. Thus, exact and accurate results can be obtained for practical applications by the proposed algorithm. Adjustment effects of the DC converters' ULTCs tap values are included in the Jacobian matrix instead of the bus admittance matrix in the sequential AC power flow algorithm as well as other ULTCs in AC system. To this aim, new equations for the calculation of power and Jacobian matrix elements are obtained for the AC system. The proposed approach is tested on the modified IEEE 17‐bus AC–DC test system. Numerical results show that the proposed approach is accurate and reliable in convergence. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Discontinuity correction in piecewise‐linear models of oscillators for phase noise characterization

Decomposition of noise perturbation along Floquet eigenvectors has been extensively used in order to achieve a complete analysis of phase noise in oscillator. Piecewise‐linear approximation of nonlinear devices is usually adopted in numerical calculation based on multi‐step integration method for the determination of unperturbed oscillator solution. In this case, exact determination of the monodromy matrix can be hampered by the presence of discontinuities between models introduced by the approximation. In this paper we demonstrate that, without the proper corrections, relevant errors occur in the determination of eigenvalues and eigenvectors, if adjacent linear models presents discontinuities. We obtain this result by the analysis of a simple 2‐D oscillator with piecewise‐linear parameter. We also demonstrate that a correct calculation can be achieved introducing properly calculated state vector boundary conditions by the use of interface matrices. This correction takes into account the effects of discontinuities between the linear models, leading to exact calculation of eigenvalues and eigenvectors, and, consequently, of the phase noise spectrum. Copyright © 2006 John Wiley & Sons, Ltd.     

A new false‐root identification method based on two‐terminal fault location algorithm for double‐circuit transmission lines

A fault location algorithm without synchronization for double‐circuit transmission lines does not require sampling synchronization, reduces the cost, and has a higher engineering value, but the algorithm still needs to be improved in the false‐root identification. This paper conducts further studies on this issue. First, the false‐root problem of the fault location algorithm without synchronization is analyzed, and then a new false‐root identification method is proposed, which is based on the difference of the existence of the false root in the calculation of the voltage amplitude along the line with different electrical moduli. It can solve the problem of the traditional method, which cannot distinguish between voltage amplitudes when they are close. Second, considering the shortcoming of the existing phase‐mode transformation matrix, a new phase‐mode transformation matrix applied to double‐circuit lines is deduced, which is based on the six‐sequence component method; it can be combined with the new false‐root identification method, thereby realizing false‐root identification under various types of faults. Finally, fault location is realized by using the moduli in the mold domain. The principle does not need to synchronize data in two terminals and is not affected by the fault types, fault resistances, and other factors. As is shown in a large number of Alternative Transients Program version of Electro‐Magnetic Transients Program (ATP‐EMTP) simulation results, the fault location has a higher accuracy © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A new under‐voltage load shedding scheme for islanded distribution system based on voltage stability indices

Under‐voltage load shedding (UVLS) is an important technique to maintain the voltage stability and frequency of a power system network. UVLS has been applied widely in transmission systems to avoid system blackouts. However, with increasing penetration of distributed generation such as photovoltaic (PV) systems, the application of UVLS becomes important for islanded distribution systems. Under this condition, the network does not have a frequency reference as when it is connected to the grid. In this condition, when the load demand exceeds the PV capacity, UVLS is the only option to stabilize the system by shedding the load based on the changes of the voltage magnitude. In this work, a new UVLS scheme based on voltage stability indices is proposed. Four voltage stability indices are used as indicators for load shedding. Based on the stability indices, the loads that have the highest tendency of voltage collapse shall be the first ones to be shed. The proposed scheme is tested on a practical distribution network energized by a grid, a mini hydro generator, and a PV system. The test results on various scenarios prove that the proposed method is able to restore the system stability. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A novel probabilistic neural network‐based algorithm for classifying internal fault in transformer windings

The major function of protective devices in a power system is to detect the occurrence of faults and to isolate the faulty sections from the rest of the system. Much progress has been made in the development algorithms for detecting faults in power transformers, which depend on transients‐based techniques. This paper presents an algorithm based on a combination of discrete wavelet transforms and probabilistic neural networks (PNNs) for classifying internal faults in a two‐winding three‐phase transformer. Fault conditions of the transformer are simulated using alternative transients program/electromagnetic transients program (ATP/EMTP) in order to obtain current signals. The mother wavelet Daubechies4 is employed to decompose the high‐frequency components from these signals. All three phases of the differential current signals are used in the fault detection decision algorithm. The variations of first‐scale high‐frequency component that detects fault are used as an input for the training pattern. The training process for the neural network and fault diagnosis decision is implemented using toolboxes on MATLAB/Simulink. Various cases and fault types based on the Thailand electricity transmission and distribution systems are studied to verify the validity of the algorithm. Backpropagation neural network is also compared with the PNN in this paper. It is found that the proposed method gives satisfactory accuracy with less training time, and will be particularly useful in the development of a modern differential relay for a transformer protection scheme. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Impact of distributed generation on transient‐based fault location techniques in distribution networks

This paper demonstrates the effect of conventional distributed generation (DG) on fault location techniques based on transient signal analysis. DG penetration in distribution networks deviates the route‐specific frequencies generated by fault traveling waves propagating along the feeders and laterals. The amount of these deviations is proportional to the rated power of a certain DG unit. A validated fault location procedure is used to clarify this effect. Fault‐generated voltage transient signals are analyzed using continuous wavelet transform (CWT). These signals are captured by a recording device generally placed at the main feeder supplying the distribution systems. The route‐specific frequencies are acquired by the wavelet amplitude spectrum of transient signals. Using this technique, the relevance between the CWT‐recognized specific frequencies and those attained by mathematical definition determines the fault position. A six‐bus radial test distribution feeder is simulated within the EMTP‐RV program, and analysis of relevant transient signals is carried out using MATLAB programming language. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A multi‐objective optimization model for determining urban energy systems under integrated energy service in a specific area

The integrated energy service system for a specific area is supposed to deliver electric and thermal energy in an integrated manner for the purpose of reducing cost, primary energy consumption, and CO₂ emission. Under an assumption of the service system, this paper develops a multi‐objective optimization model for determining urban energy systems. Considering the various energy system alternatives, such as photovoltaic generations for residential houses and fuel‐cell cogenerations for business and commercial customers, the model determines the share of the energy system alternatives in order to minimize the above three indices. As numerical examples, this paper illustrates trade‐off analyses in the case when the proposed model is applied to a 2 km × 2 km square area in Osaka. Finally, this paper illustrates the role of various energy system alternatives from CO₂ reduction and fossil energy reduction points of view. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 147(3): 20–31, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10275     

A study on collaborative operation method for a new energy type dispersed power supply system by AC‐EMAP model

Application of a dispersed power supply system consisting of a large‐scale photovoltaic system (PV), a fuel cell (FC), and an electric double layer capacitor (EDLC) is studied in this paper. This system is operated in autonomous mode, taking account of time delay characteristics of FC. The modified Euler type Moving Average Prediction (EMAP) model is improved using short‐time fast Fourier transform (ST‐FFT). The Adaptive Control type EMAP (AC‐EMAP) model is introduced to reduce the capacity of EDLC. This system can meet the multi‐quality electric power requirements of customers, and improve voltage stability and uninterruptible power supply (UPS) function as well. Moreover, the required capacity of EDLC to compensate the fluctuation of both PV output and Load demand is clarified by a simulation based on collaborative operation method by a prediction model using software MATLAB/Simulink. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 156(1): 13–24, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20262