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SICE Journal of Control, Measurement, and System Integration Vol. 5 (2012), No. 4

A Study on Sequence Generation Powers of Small Cellular Automata

Naoki KAMIKAWA, Hiroshi UMEO

pp. 191-199

Abstract

A model of cellular automata (CA) is considered to be a well-studied non-linear model of complex systems in which an infinite one-dimensional array of finite state machines (cells) updates itself in a synchronous manner according to a uniform local rule. A sequence generation problem on the CAs has been studied and many scholars proposed several real-time sequence generation algorithms for a variety of non-regular sequences such as prime, Fibonacci, and {2n|n=1,2,3,...} sequences etc. The paper describes the sequence generation powers of CAs having a small number of states, focusing on the CAs with one, two, and three internal states, respectively. The authors enumerate all of the sequences generated by two-state CAs and present several non-regular sequences that can be generated in real-time by three-state CAs, but not generated by any two-state CA. It is shown that there exists a sequence generation gap among the powers of those small CAs.

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A Study on Sequence Generation Powers of Small Cellular Automata

Conversion of Linear Time-Invariant Delay-Differential Equations with External Input and Output into Representation as Time-Delay Feedback Systems

Tatsuya YAMAZAKI, Tomomichi HAGIWARA

pp. 200-209

Abstract

A new stability analysis approach of time-delay systems (TDSs) called the monodromy operator approach has been developed recently. The underlying assumption of such an approach is that a TDS is represented as a time-delay feedback system Σ consisting of a finite-dimensional linear time-invariant (FDLTI) system F and a pure-delay H. Aiming at supplementing a procedure with which this approach can be applied also to TDSs described by delay-differential equations (DDEs), this paper studies the conversion problem of an LTI DDE with external input and output into representation as the time-delay feedback system Σ. As a very important preparation for such a study, this paper first introduces two different definitions of the solutions to such DDEs, assuming a general situation that their initial functions are possibly discontinuous. It is then shown that their solution in the sense of the first definition can be represented as a part of the output of the finite-dimensional part F in an appropriately constructed time-delay feedback system Σ with a suitably determined initial condition. Similarly, it is also shown that the solution in the second sense can be converted into representation as the state of F in a differently constructed Σ with another initial condition. Illustrative examples are also provided for each of the two conversion methods.

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Conversion of Linear Time-Invariant Delay-Differential Equations with External Input and Output into Representation as Time-Delay Feedback Systems

Rough Set Based Optimization for Data Mining: An Improved Fuzzy Clustering Approach

Jianxiong YANG, Junzo WATADA

pp. 210-217

Abstract

The objective of this paper is to provide an improved fuzzy clustering approach to data mining. The method consists of fuzzy clustering and rough set model that together deal with the uncertainty of data. To describe the proposed method, the rough set model is used to optimize the mined knowledge, then after embedding the sample data for data mining, fuzzy clustering is applied to cluster the target data by sample data to extract desired data. The process behind algorithm and its applicability are illustrated through an application of the proposed method to the knowledge mining of accident cases, and this shows that improved fuzzy clustering should have wider-ranging applications.

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Rough Set Based Optimization for Data Mining: An Improved Fuzzy Clustering Approach

Sum of Squares Based Input-to-State Stability Analysis of Polynomial Nonlinear Systems

Hiroyuki ICHIHARA

pp. 218-225

Abstract

Input-to-state stability (ISS) is an advanced concept of stability for nonlinear systems in the sense that the input to the system is taken into account. This paper proposes a numerically tractable condition to analyze ISS for polynomial nonlinear systems. The condition is formulated as a sum of squares (SOS) problem that is a feasibility problem including SOS polynomials. A solution of the problem is obtained by solving a semidefinite programming problem. The key technique is to formulate class K functions, which have the inverse map on real nonnegative region, as polynomials. This paper also gives numerically tractable ISS conditions for the cascade connection of subsystems and for the feedback interconnected system. A few examples are shown to illustrate our analysis conditions.

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Sum of Squares Based Input-to-State Stability Analysis of Polynomial Nonlinear Systems

Localization of a Radio-Frequency Identification Tag from Measurements of the Fourier Coefficients of Its Magnetic Flux Density

Takaaki NARA, Yuushi TAKANASHI, Hirotoshi WATANABE

pp. 226-232

Abstract

This paper presents a method for estimating the position of a radio-frequency identification (RFID) tag in two-dimensional (2D) space. A low-frequency (135 kHz), passive RFID tag with a loop antenna transmits its ID number to the tag reader by electromagnetic induction. This study reveals that the radial distance and the azimuth of the RFID tag in a 2D plane can be determined from the absolute value and phase of the first-order Fourier coefficient of the magnetic flux density generated by the tag. The authors develop a sensor unit that consists of four coils: two special coils that generate electromotive forces that are proportional to the first-order Fourier cosine and sine coefficients and two conventional loop coils. Using the developed sensor, a 29-mm-diameter disk-shaped RFID tag can be localized with a maximum (average) error of 18 mm (5 mm) within a circular domain of radius 140 mm.

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Localization of a Radio-Frequency Identification Tag from Measurements of the Fourier Coefficients of Its Magnetic Flux Density

An On-Line Algorithm for Measuring the Translational and Rotational Velocities of a Table Tennis Ball

Chunfang LIU, Yoshikazu HAYAKAWA, Akira NAKASHIMA

pp. 233-241

Abstract

This paper proposes an on-line method for estimating both translational and rotational velocities of a table tennis ball by using only a few consecutive frames of image data which are sensed by two high speed cameras. In order to estimate the translational velocity, three-dimensional (3D) position of the ball's center at each instant of camera frame is obtained, where the on-line method of reconstructing the 3D position from the two-dimensional (2D) image data of two cameras is proposed without the pattern matching process. The proposed method of estimating the rotational velocity belongs to the image registration methods, where in order to avoid the pattern matching process too, a rotation model of the ball is used to make an estimated image data from an image data sensed at the previous instant of camera frame and then the estimated image data are compared with the image data sensed at the next instant of camera frame to obtain the most plausible rotational velocity by using the least square and the conjugate gradient method. The effectiveness of the proposed method is shown by some experimental results in the case of a ball rotated by a rotation machine as well as in the case of a flying ball shot from a catapult machine.

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An On-Line Algorithm for Measuring the Translational and Rotational Velocities of a Table Tennis Ball

Generation of Drawing Sensation by Surface Acoustic Wave Tactile Display on Graphics Tablet

Ryo TAMON, Masaya TAKASAKI, Takeshi MIZUNO

pp. 242-248

Abstract

This paper describes pen interface using a surface acoustic wave tactile display. Using the display, tactile sensation like a feeling of drawing with a charcoal can be generated. Combined with a graphics tablet with an LCD, it is possible to generate both visual information and tactile sensation dynamically. To add reality of sensation, control referring to m-sequence random number is proposed and described in this paper. Measurement results of pen vibration during rubbing the display with the reference and those without it were compared. FFT analysis results of the pen vibration are also compared.

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Generation of Drawing Sensation by Surface Acoustic Wave Tactile Display on Graphics Tablet

Low-Dimensional Feature Representation for Instrument Identification

Mizuki IHARA, Shin-ichi MAEDA, Kazushi IKEDA, Shin ISHII

pp. 249-258

Abstract

For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

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Low-Dimensional Feature Representation for Instrument Identification

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