Abstract
〈Vol.4 No.5(2011.9)〉
Titles
[Contributed Papers]
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■ Algorithm for Automatic Behavior Quantification of Laboratory Mice Using
High- Frame-Rate Videos
Hiroshima University・Yuman NIE，Takeshi TAKAKI，Idaku ISHII
and Tokyo University of Agriculture and Technology・Hiroshi MATSUDA
In this paper, we propose an algorithm for automatic behavior quantification
in laboratory mice to quantify several model behaviors. The algorithm can
detect repetitive motions of the fore- or hind-limbs at several or dozens
of hertz, which are too rapid for the naked eye, from high-frame-rate video
images. Multiple repetitive motions can always be identified from periodic
frame-differential image features in four segmented regions?the head, left
side, right side,and tail. Even when a mouse changes its posture and orientation
relative to the camera, these features can still be extracted
from the shift- and orientation-invariant shape of the mouse silhouette
by using the polar coordinate system and adjusting the angle coordinate
according to the head and tail positions. The effectiveness of the algorithm
is evaluated by analyzing long-term 240-fps videos of four laboratory mice
for six typical model behaviors: moving, rearing, immobility, head grooming,
left-side scratching, and right-side scratching. The time durations for
the model behaviors determined by the algorithm have detection/correction
ratios greater than 80% for all the model behaviors. This shows good quantification
results for actual animal testing.
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■ H∞ Design of Periodically Nonuniform Interpolation and Decimation for
Non-Band-Limited Signals
Kyoto University・Masaaki NAGAHARA,Texas Tech University・ Masaki OGURA
and Kyoto University・Yutaka YAMAMOTO
In this paper, we consider signal interpolation of discrete-time signals
which are decimated nonuniformly. A conventional interpolation method is
based on the sampling theorem, and the resulting system consists of an
ideal filter with complex-valued coefficients. While the conventional method
assumes band limitation of signals, we propose a new method by sampled-data
H∞ optimization. By this method, we can remove the band-limiting assumption
and the optimal filter can be with real-valued coefficients. Moreover,
we show that without band-limited assumption, there can be the
optimal decimation patterns among ones with the same ratio. By examples, we show the effectiveness of our method.
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■ Algorithm for Route Planning with Multiple Intermediate Destinations
Waseda University・Manoj Kanta MAINALI, Shingo MABU and Kotaro HIRASAWA
The optimal route recommendation in navigation systems is often considered
to be the optimal route recommendation between two locations, i.e., an
origin and a destination. However, in practical scenarios, traveling to
several intermediate destinations before the final destination needs to
be considered. Conventional route search algorithms cannot consider such
restrictions in the route search. In this paper, a method to find the optimal
route via several intermediate destinations is proposed. The proposed method
is divided into three steps. In the first step, the conventional route
search algorithm is used to find the optimal traveling time and optimal
route among the origin, intermediate destinations and final destination.
In the second step, the visiting order of the intermediate destination
is optimized using the population based RasID-D (RasID-DP) to minimize
the total traveling time. Finally, the optimal route from the origin to
destination is determined based on the results of the previous steps. The
proposed method is evaluated based on the efficiency of the
optimization of the visiting order of intermediate destinations. Simulation
results show that RasID-DP based optimization can find better solutions
efficiently.
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■ A Fast Computation for the State Vector in a Max-Plus Algebraic System
with an Adjacency Matrix of a Directed Acyclic Graph
Nagaoka University of Technology・Hiroyuki GOTO
We provide a useful method for calculating the state vector of a state
equation efficiently in a max-plus algebraic system. For a discrete event
system whose precedence relationships are represented by a directed acyclic
graph, computing the transition matrix, which includes the Kleene star
operation of a weighted adjacency matrix, is occasionally the bottleneck.
On the other hand, the common objective is to compute the state equation,
rather than the transition matrix itself. Since the state equation is essentially
the multiplication of the transition matrix and vector, we propose algorithms
for efficiently calculating the multiplication and left division of the
Kleene star of an adjacency matrix and a vector.
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■ Worst-Case Performance Analysis of Multi-Mode Switching Control Systems
with a Strategy Consisting of Maximal Output Admissible Setss
Nara Institute of Science and Technology・Kiminao KOGISO and
Nagaoka University of Technology・Kenji HIRATA
This paper proposes a method for evaluating control performance of a switching
control system for which the switching strategy consists of so-called maximal
output admissible sets. The proposed method gives an upper bound of the
control performance index. The key to calculate it is the use of a dwell
time. Two types of the algorithms are presented so as to seek for the dwell
time. The proposed method is summarized as a theorem that provides an upper
bound of the control performance index. Finally, a numerical example is
used to make sure of what the theorem states.
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■ Graphical Design Software for Dynamic Quantizers in Control Systems
Kyoto University・Ryosuke MORITA, Shun-ichi AZUMA
, Maizuru National College of Technology・Yuki MINAMI
and Kyoto University・and Toshiharu SUGIE
This paper presents a software tool, entitled ODQLab, to design dynamic
quantizers for discrete-valued input control. ODQLab is a Matlab-based
graphical tool, which enables us to obtain and verify dynamic quantizers
without the knowledge of any sophisticated design theory. In this paper,
we introduce the software tool with the underlying theory. Its effectiveness
is demonstrated by design examples and experimental evaluations.
▲ ■ A Note on the Minimum Number of the Actuators for Stabilization in Linear
Parabolic Boundary Control Systems
Kobe University・Takao NAMBU
In the stabilization problem for linear boundary control systems of parabolic
type, we have just recently obtained a criterion on the smallest number
of the sensors. We show in this note that a similar result holds on the
number of the actuators, the best case of which is equal to 1, necessary
for stabilization.
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■ Feature Extraction from Subband Brain Signals and Its Classification
University of Electro-Communications・Manoj Kumar MUKUL and
Kyoto University・ Fumitoshi MATSUNO
This paper considers both the non-stationarity as well as independence/uncorrelated
criteria along with the asymmetry ratio over the electroencephalogram (EEG)
signals and proposes a hybrid approach of the signal preprocessing methods
before the feature extraction. A filter bank approach of the discrete wavelet
transform (DWT) is used to exploit the non-stationary characteristics of
the EEG signals and it decomposes the raw EEG signals into the subbands
of different center frequencies called as rhythm. A post processing of
the selected subband by the AMUSE algorithm (a second order statistics
based ICA/BSS algorithm) provides the separating matrix for each class
of the movement imagery. In the subband domain the orthogonality as well
as orthonormality criteria over the whitening matrix and separating matrix
do not come respectively. The human brain has an asymmetrical structure.
It has been observed that the ratio between the norms of the left and right
class separating matrices should be different for better discrimination
between these two classes. The alpha/beta band asymmetry ratio between
the separating matrices of the left and right classes will provide the
condition to select an appropriate multiplier. So we modify the estimated
separating matrix by an appropriate multiplier in order to get the required
asymmetry and extend the AMUSE algorithm in the subband domain. The desired
subband is further subjected to the updated separating matrix to extract
subband sub-components from each class. The extracted subband sub-components
sources are further subjected to the feature extraction (power spectral
density) step followed by
the linear discriminant analysis (LDA).
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■ Bridge Diagnosis by Using Nonlinear Independent Component Analysis and
Displacement Analysis
Shanghai University・Juanqing ZHENG,
Waseda University・Yichun YEH and Harutoshi OGAI
A daily diagnosis system for bridge monitoring and maintenance is developed
based on wireless sensors, signal processing, structure analysis, and displacement
analysis. The vibration acceleration data of a bridge are firstly collected
through the wireless sensor network by exerting. Nonlinear independent
component analysis (ICA) and spectral analysis are used to extract the
vibration frequencies of the bridge. After that, through a band pass filter
and Simpson’s rule the vibration displacement is calculated and the vibration
model is obtained to diagnose the bridge. Since linear
ICA algorithms work efficiently only in linear mixing environments, a nonlinear
ICA model, which is more complicated, is more practical for bridge diagnosis
systems. In this paper, we firstly use the post nonlinear method to change
the signal data, after that perform linear separation by FastICA, and calculate
the vibration displacement of the bridge. The processed data can be used
to understand phenomena like corrosion and crack, and evaluate the health
condition of the bridge. We apply this system to Nakajima Bridge in Yahata,
Kitakyushu, Japan.
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■ Novel ODE-Type Smith Predictor for Nonlinear Control Systems with Delay
Hokkaido University・Xuanxuan TENG and Yuh YAMASHITA
This paper proposes a novel ODE-type Smith predictor for nonlinear control
systems with transmission delays.The presence of time delays in the transmission
of the control signals and the sensor signals may severely affect the performance
of the closed-loop system and prevent the successful application of established
nonlinear control methodologies.First, we investigate a backstepping interpretation
of Smith predictors for linear time-variant (LTV) systems in the state
space. Second, we propose a new nonlinear Smith predictor, the error dynamics
of which is locally stabilized by another Smith predictor for the LTV systems.
The Smith predictor can reduce the computational cost of the controller,because
integral equations, which should be solved at each time in previously proposed
predictive controllers, are replaced by inner-product operations.
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