An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Nonlinear and Adaptive Control Design [Book Review]

This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

Disclosed is an apparatus for use in wireless energy transfer, which includes a first resonator structure configured to transfer energy non-radiatively with a second resonator structure over a distance greater than a characteristic size of the second resonator structure. The non-radiative energy transfer is mediated by a coupling of a resonant field evanescent tail of the first resonator structure and a resonant field evanescent tail of the second resonator structure.

Wireless energy transfer

The electromagnetic energy transfer device includes a first resonator structure receiving energy from an external power supply. The first resonator structure has a first Q-factor. A second resonator structure is positioned distal from the first resonator structure, and supplies useful working power to an external load. The second resonator structure has a second Q-factor. The distance between the two resonators can be larger than the characteristic size of each resonator. Non-radiative energy transfer between the first resonator structure and the second resonator structure is mediated through coupling of their resonant-field evanescent tails.

Wireless non-radiative energy transfer

This paper presents a new control scheme for a Class DE inverter, that is, frequency modulation/pulsewidth modulation (FM/PWM) control. Further, the FM/PWM controlled Class DE inverter is analyzed and we clarify performance characteristics. Since the FM/PWM controlled inverter has two control parameters, namely, the switching frequency and the switch-on duty ratio, it has one more degree of freedom for the control than the inverter with the conventional control scheme. The increased degree of freedom is used to minimize the switching losses. Therefore, it is possible to control the output power with high power-conversion efficiency for wide-range control. Carrying out the circuit experiments, we confirm that the experimental results agree well with the theoretical predictions quantitatively. For example, the proposed controlled inverter can control the output voltage from 56% to 191% of the optimum one, which is designed for 1.8 W at 1.0 MHz, with maintaining over 90% power-conversion efficiency.

FM/PWM control scheme in class DE inverter

The face is a complex multidimensional visual model and developing a computational model for face recognition is difficult. In this paper, we present a method for face recognition based on parallel neural networks. Neural networks (NNs) have been widely used in various fields. However, the computing efficiency decreases rapidly if the scale of the NN increases. In this paper, a new method of face recognition based on fuzzy clustering and parallel NNs is proposed. The face patterns are divided into several small-scale neural networks based on fuzzy clustering and they are combined to obtain the recognition result. In particular, the proposed method achieved a 98.75% recognition accuracy for 240 patterns of 20 registrants and a 99.58% rejection rate for 240 patterns of 20 nonregistrants. Experimental results show that the performance of our new face-recognition method is better than those of the backpropagation NN (BPNN) system, the hard c-means (HCM) and parallel NNs system, and the pattern-matching system

A Method of Face Recognition Based on Fuzzy c-Means Clustering and Associated Sub-NNs

It is well known that sliding mode control (SMC) is capable of tackling systems with uncertainties. However, the discontinuous control signal causes a significant problem of chattering. In this paper, a new and simple approach to chattering free SMC methodology is proposed. The main purpose is to eliminate the chattering phenomenon. As a result, the chattering is eliminated and error performance of sliding mode control is improved. The reduction of the chattering of sliding mode control is achieved by using a distance function which measure the distance between the trajectory of state errors and the sliding surface as the corrective control term instead of discontinuous sign function. Experimental study carried out on a magnetic levitation system is presented. Experiments verified that the proposed control has the advantage of less chattering in SMC.

/pdf/chattering-free-sliding-mode-control-in-magnetic-levitation-gj5ohy0f05.pdf

Chattering Free Sliding Mode Control in Magnetic Levitation System

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

https://www.onlinelibrary.wiley.com/doi/pdf/10.1002/eej.20486

Noise removal for medical X‐ray images in wavelet domain

This paper presents a new method for self-tuning control of nonminimum phase discrete-time stochastic systems using approximate inverse systems obtained from the least-squares approximation. We show how unstable pole-zero cancellations can be avoided, and that this method has the advantage of being able to determine an approximate inverse system independently of the plant zeros. The proposed scheme uses only the available input and output data and the stability using approximate inverse systems is analyzed. Finally, the results of computer simulation are presented to show the effectiveness of the proposed method

Jianming Lu

Papers

FM/PWM control scheme in class DE inverter

A Method of Face Recognition Based on Fuzzy c-Means Clustering and Associated Sub-NNs

Chattering Free Sliding Mode Control in Magnetic Levitation System

Noise removal for medical X‐ray images in wavelet domain

On Self-Tuning Control of Nonminimum Phase Discrete-Time Systems Using Approximate Inverse Systems