Abstract
〈Vol.5 No.4(2012.7)〉
Titles
[Contributed Papers]
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■ A Study on Sequence Generation Powers of Small Cellular Automata
Osaka Electro-Communication・Naoki KAMIKAWA and Hiroshi UMEO
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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■ Conversion of Linear Time-Invariant Delay-Differential Equations with
External Input and Output into Representation as Time-Delay Feedback Systems
Kyoto University・Tatsuya YAMAZAKI and Tomomichi HAGIWARA
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 timedelay
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 delaydifferential
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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■ Rough Set Based Optimization for Data Mining: An Improved Fuzzy Clustering
Approach
Waseda University・Jianxiong YANG, and Junzo WATADA
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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■ Sum of Squares Based Input-to-State Stability Analysis of Polynomial
Nonlinear Systems
Meiji University・Hiroyuki ICHIHARA
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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■ Localization of a Radio-Frequency Identification Tag from Measurements
of the Fourier Coefficients of Its Magnetic Flux Density
The University of Electro-Communications・Takaaki NARA,
Yuushi TAKANASHI and Hirotoshi WATANABE
This paper presents a method for estimating the position of a radio-frequency
identification (RFID) tag in twodimensional (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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■ An On-Line Algorithm for Measuring the Translational and Rotational
Velocities of a Table Tennis Ball
Nagoya University・Chunfang LIU,
Nagoya University and RIKEN-TRI Collaboration Center・Yoshikazu HAYAKAWA, and Nagoya University・Akira NAKASHIMA
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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■ Generation of Drawing Sensation by Surface Acoustic Wave Tactile Display
on Graphics Tablet
Saitama University・Ryo TAMON，Masaya TAKASAKI and Takeshi MIZUNO
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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■ Low-Dimensional Feature Representation for Instrument Identification
The MathWorks GK・Mizuki IHARA, Kyoto University・Shin-ichi MAEDA,
Nara Institute of Science and Technology・Kazushi IKEDA, and Kyoto University・Shin
ISHII
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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