bluuebunny/crossref_metadata_2025 huggingface dataset:
An age replacement policy for a hard disk considering failures of sectors
Authors: Hirakoshi Hiroyuki , Sandoh Hiroaki
Published: July 2007

Hard disk drives are an indispensable element of modern computer systems and their failure often causes loss of precious data. Hard disks are encapsulated to prevent contamination; a defect of any of the encapsulated mechanical components means that no data can be accessed. Another type of hard disk effect is disk sector failure: in this case only a relatively small amount of data can be lost and the failed sector can be replaced by a spare sector. This ensures that the drive is fully functional. However, the number of spare sectors is limited: If the number of failed sectors exceeds it, the drive is written off. This paper, taking into consideration the forementioned two drive‐defect types, discusses a strategy for preventive replacement of hard disk drives. Expected replacement cost is expressed analytically, and the function is then minimized, leading to the optimum age replacement strategy in terms of cost.
Speech coding based on adaptive mel‐cepstral analysis and its evaluation
Authors: Tokuda Keiichi , Kobayashi Takao , Imai Satoshi , Fukada Toshiaki
Published: July 2007

This paper proposes the ADPCM speech coding system using mel‐cepstrum as the parameter for the short‐term prediction. In the proposed coding system, the backward type adaptive prediction is applied based on the adaptive mel‐cepstrum analysis. Operations such as noise shaping and postifitering are executed through the melcepstrum. Consequently, it is expected that the noise shaping and the postfiltering have the effect which is matched to the human auditory characteristics.

This paper presents the configuration of the coding system with some improvements such as the addition of the pitch predictor, and the quality of the coded speech is evaluated. It is shown as a result that the proposed coding system realizes the same speech quality at 16 kbit/s as that of the 32‐kbit/s ADPCM, even though there is no algorithm delay.
NP‐completeness of interval graph completion from a path graph
Authors: Yamaguchi Kazuaki , Araki Toshiro , Kashiwabara Toshinobu
Published: July 2007

Given a set of paths on a tree, the graph with vertices corresponding to the paths, where the corresponding vertices are connected by an edge when two paths intersect, is called the path graph. Given a set A of finite intervals on a straight line, the graph with vertices corresponding to the intervals belonging to A, where an edge is provided when two intervals intersect, is called the interval graph.

In this paper, it is shown that the problem to decide whether or not a given path graph can be converted to an interval graph by adding K or less edges is NP‐complete.
Decoding mechanism of a scarce state transition‐type viterbi decoder for general nonsystematic convolutional codes and its asymptotic behavior on a very noisy channel
Authors: Tajima Masato
Published: July 2007

When a scarce state transition (SST) Viterbi decoder is used to decode general nonsystematic convolutional codes (not included among quick look‐in (QLI) codes), metrics based on the maximum a posteriori probability (MAP) estimation method must be computed in order for the main decoder to operate under the criterion of minimizing the decoding error probability. In this case, however, it becomes necessary to extend the original code trellis structure by introducing augmented trellis states in order to incorporate the newly induced correlation among the apparent information sequence.

This paper shows that the extended trellis degenerates into the original one as the channel error probability q approaches one‐half. By performing an equivalent transformation of metrics, it is shown also that the branch metrics derived based on the MAP estimation method converge to those computed using the conventional one as q approaches one‐half.
Stabilization of the saddle‐type periodic points in phase‐locked loop equation by the OGY‐control method
Authors: Ogawa Takeo , Endo Tetsuro
Published: July 2007

It is well known that the differential equation representing the phase‐locked loops (PLL) can produce chaotic attractor. In particular, since the periodic solution of the second type representing the out‐of‐lock condition can bifurcate to become chaos easily by small external force so its theoretical treatment is possible. Moreover, much research activity has been performed in this area and various interesting points have been confirmed by laboratory experiments.

This paper is an attempt to stabilize various saddletype periodic orbits included in the chaotic attractor bifurcated from second‐type periodic solutions by the OGY method. In general, a chaotic attrrator includes a number of saddle‐type periodic orbits, and if one wants to stabilize one of them by the OGY method, one must know various values, e.g., coordinates and eigenvalues, etc., of the periodic points on the Poincaré map. However, there is no method to determine these values, in general.

The authors obtained the saddle‐type 1‐, 2‐, 3‐, 4‐, and 8‐periodic orbits included in the chaotic attractor by using the continuation method. By applying the continuation method to the 1‐parameter bifurcation diagram, all parameter values required in the OGY method were determined and stabilization of any one of them was dethonstrated by computer simulation. In particular, the authors tested two OGY methods for N‐periodic orbits. One method needs one change of the control parameter after N mappings of external force, and the second method changes the parameter at every mapping. It was confirmed that the latter method takes a shorter time to achieve control.
Weak formulation of stochastic parabolic systems with subdifferential boundary conditions
Authors: Ishikawa Masaaki
Published: July 2007

This paper discusses the mathematical formulation of the stochastic parabolic system, which is described by the multivalued operator called subdifferential operator, that plays an important role in the modeling of the free boundary problem such as viscoelastic and obstacle problems. For various deterministic distributed systems containing a subdifferential operator, the existence of the strong or weak solution is already shown.

With respect to the stochastic distributed system, on the other hand, the existence of a strong solution has not been shown except for the system containing a subdifferential operator of a special convex function. As to the existence of the weak solution, there is a report of the case where the subdifferential operator appears in the interior of the system, but there is no report on the general stochastic system containing a subdifferential operator in the boundary condition. Another point is that a strong constraint is imposed on the initial value and the input function in the proof for the existence of the strong solution.

From those viewpoints, this paper aims at ameliorating such a constraint and formulates the system by the weak solution. First, the existence condition for the weak solution is shown. Then it is shown that there exists the maximal solution in the set of weak solutions and an estimate for the maximal solution is derived which has a stronger significance than in the past formulation.
Chaos and fractal properties in EEG data
Authors: Ogo Kiyotaka , Nakagawa Masahiro
Published: July 2007

The purpose of this study is to verify that EEG is composed of frequency components with chaotic characteristics. EEG data are decomposed into frequency components, and the chaos and fractal analyses are applied. More precisely, the running spectrum of EEG is derived and the chaos analysis is applied using the Lyapunov spectrum and the correlation dimension. As a result, the existence of the chaotic phenomenon is verified for most of the frequency components used as the objects of the analysis. It is found also that the fractal properties exist in most of the frequency components. the multifractal analysis is applied to the EEG data, and the generalized dimension of q‐th order is determined. It is seen as a result that the reconstruction attractors of EEG are placed by a nonuniform fractal distribution, which is represented by a large number of scaling indices concerning the dimension.
Optimal checkpointing procedures taking into account system failure caused by checkpointing
Authors: Yanagihara Masayoshi , Odagiri Masanori , Osaki Shunji , Kaio Naoto
Published: July 2007

In the past studies of checkpointing for the computer system, the event that a system failure may be generated due to the checkpointing has not been considered. In practice, it is highly probable that this kind of failure arises in the checkpointing.

From such a viewpoint, this paper considers the event where a failure due to the checkpointing is produced at the time of checkpointing and proposes a procedure to derive the optimal checkpointing sequence as the optimal checkpointing strategy. As the evaluation function, the expected cost per cycle and the expected cost per unit time in the steady state are used. the optimal checkpointing strategy is considered to minimize the expected cost.

Finally, numerical investigation is made assuming the exponential and the Weibull distributions as the failure time distribution.
Aircraft collision avoidance with potential gradient—ground‐based avoidance for horizontal maneuvers
Authors: Miura Akira , Morikawa Hiroyuki , Mizumachi Moriyuki
Published: July 2007

This paper describes ground‐based avoidance for horizontal maneuvers using a concept of potential as a collision avoidance aircraft procedure. First, mathematical formulation is introduced by using potential as a way to systematically represent the conditions contributing to collision avoidance such as a threat of collision with other aircraft and degrees of deviation from the original course.

The flight course with a lower potential is considered safer. In the choice of a specific avoidance course, an avoidance pattern generation method by means of potential gradient is shown. the future location of the aircraft is sampled at a certain time interval. the shift of the sampling point corresponding to the potential gradient at each sampling point or the force applied to each sampling point (attractive or repulsive) is repeated.

It was confirmed that by means of this method, avoidance patterns without danger of collision can be obtained with only horizontal avoidance except for special cases. However, when the sampling points are symmetric or when more than three aircraft are involved, the procedure is not adequate and some provisions are needed. to this end, the sampling point arrangement in the initial stage before the avoidance pattern is formed and the three‐dimensional avoidance including vertical avoidance can be considered.
Computer graphics eye‐animation and feeling of gaze line
Authors: Morii Kiyohiro , Kishino Fumio , Tetsutani Nobuji
Published: July 2007

In a teleconferencing system with realistic sensations, human images are generated by computer graphics (CG). This requires animating natural eye movement with CG. This paper describes a real‐time animation technique to generate blinking and gaze shift, while still considering convergence using a graphic workstation. Moreover, the feeling of eye contract is evaluated using this animation. In this experiment, the gaze generated by CG using two‐dimensional (2‐D) or 3‐D display is evaluated subjectively and compared with the gaze of an actual person. Also, an experiment is performed on the time required for perception of eye contact when the eyes of the CG image are moving. Then, a real‐time CG eyeanimation system combined with an eye‐movement detector is described. Also, the allowable transmission delay time when using this system is evaluated subjectively.
Applications of safety index for fault analysis system
Authors: Mineo Yoshiyuki , Suzuki Yoshihisa
Published: July 2007

The safety index is proposed as an index for system reliability. In order to determine this index, the tree analysis for safety (TAS) must be constructed for the individual system. This paper focuses on the hazard source of the fault analysis (FA) system and discusses a method to construct standard TAS, which is independent of the system configuration of the FA system. As a first step, the hazard sources of the FA system are divided into two classes. One is the class in which the existence of the hazard source itself is the problem, and the source must be deleted from the viewpoint of safety (explicit hazard source). the other is the class where the hazard source is indispensable to the FA system; however, a serious event may be produced if an explicit hazard source is generated (potential hazard source). the case where the potential hazard source in the FA system induces an accident is defined as the standard model. the standard TAS is constructed. By providing a selection branch at the lowest level node of TAS, a TAS aligned to the checklist is constructed. By those approaches, it is made possible that a beginner unfamiliar with TAS can determine the safety index. In other words, the safety index is now a useful criterion for the safety evaluation of the FA system.
Two‐step pulse width modulation sinusoidal inverter with modulation switching and frequency spectra
Authors: Arimoto Hideki , Umeda Hisakazu , Yamauchi Yukiji , Kaku Shukichi
Published: July 2007

The pulse width modulation (PWM) in the inverter is an extremely important technology in power electronics. One of the problems in the PWM inverter is the existence of unwanted harmonics caused by switching. In this paper, a method to reduce this unwanted harmonic component, a modulation switching method, is proposed in which the modulation method is switched t the locations such as the peak of the reference sinusoidal signal. the PWM wave train is analyzed by a computer simulation as well as the theoretical analysis by the double Fourier series expansion. It is shown that the present method is effective in the reduction of the unwanted harmonic. Next, the characteristics of the modulation switching two‐stage PWM sinusoidal inverter are investigated.
Computer simulation on nonlinear interaction of intense microwave with space plasmas
Authors: Matsumoto Hiroshi , Hashino Yoshitaka , Yashiro Hiroyuki , Shinohara Naoki , Omura Yoshiharu
Published: July 2007

The concept of a solar power station (SPS) was proposed 25 years ago. During the intervening years, long‐distance, high‐power transmission microwave technology has advanced. Realization of wireless power transmission in space is now no longer a dream. It has been predicted from three‐way coupling that a static plasma wave is excited when an intense microwave passes through space plasma. the microwave power transmission rocket experiment in an ionosphere carried out by the authors (MINIX, Microwave Ionosphere Nonlinear Interaction experiment) has confirmed this fact. In this experiment, a phenomenon that cannot be explained by the three wave resonance theory has been discovered. In this paper, a computer experiment using plasma has been carried out with an electromagnetic particle code. Static plasma wave excitation and the saturation phenomenon are explained in which not only the simple three‐wave coupling but also the wave‐particle interaction are included.
Complex chebyshev approximation for infinite impulse response digital filters
Authors: Okuda Masahiro , Ikehara Masaaki , Takahashi Shin‐Ichi
Published: July 2007

In this paper, a new Chebyshev approximation (amplitude and phase simulataneous approximation) method for IIR digital filters is proposed. the proposed algorithm is based on the Remez algorithm. By solving the eigenvalue problem at each iteration, the frequency characteristic of the filter is interpolated so that the error function in the complex domain is made with equal ripples. Since the previously proposed amplitude and phase simulataneous approximation methods for the IIR digital filters are based on the nonlinear equation, they all require substantial computation. On the other hand, the present method is extremely simple and the amount of compuation can be reduced singnificantly. Nevertheless, the performance equal to or more than the conventional one can be obtained. Further, the present method can be applied not only for the real coefficient filters but also for the complex coefficient filtes. It is possible to carry out characteristic approximation limited to the positive frequency range. Hence, a further reduction of the filter order needed for signal processing can be attempted.
Optimal design of system reliability by an improved genetic algorithm
Authors: Yokota Takao , Gen Mitsuo , Ida Kenichi , Taguchi Takeaki
Published: July 2007

When genetic algorithms are applied to large‐scale optimization problems taking only integer‐valued solutions, too often the chromosomes generated fail to satisfy the constraint conditions. In such cases, the selection operator is unable to produce high‐quality chromosomes, worsening the search efficiency. As a consequence, many times good solutions cannot be obtained. In this paper, in order to cope with such a problem, a new algorithm with improved chromosome selection mechanism is proposed, taking into account the evaluation function including some information about chromosomes not contained in the feasible region of the nonlinear integer programming problem under consideration. The proposed method considers how far each unfeasible chromosome is from the feasible region. The improved algorithm was applied to a large‐scale problem of optimal design of system reliability formulated as a nonlinear integer programmng problem and numerical experiments confirmed the effectiveness of the method.
An optimal design of differentiators by recursive narrowband filters
Authors: Tachibana Yasuo , Maniwa Hisakazu , Kameda Hiroshi , Kondo Michimasa
Published: July 2007

This paper proposes a narrowband filter, which is a finite impulse response (FIR) filter where the phase response exhibits a constant phase‐linear characteristic, independently of the center frequency, and the execution format is a sum of stable recursive filters. the optimal design of the differentiator (differentiation filter) using that narrowband filter is discussed.

To realize a sharp narrowband characteristic, higher‐order FIR filters are needed. the narrowband filter proposed in this paper has the feature that it is the sum of the recursive filters, and the operation can be executed with the number of operations which is independent of the order. the filter considered is obtained as a linear combination of a number of narrowband filters with distributed center frequencies.

By connecting the first‐order sum or difference filter in series to the above filter, a filter can be constructed which has an arbitrary amplitude response and approximately constant linear‐phase response. Especially, the optimal design procedure is given for the set of bandpass differentiator filters and application examples are shown for the estimation of the transfer function of the linear system.
Bifurcation sets in forced rayleigh oscillator containing a diode
Authors: Inaba Naohiko , Baba Norio , Ohnishi Masafumi
Published: July 2007

The forced Rayleigh equation is known as the differential equation for which the existence of the aperiodic solution is shown for the first time. From the viewpoint of the history of the research of chaos, it is very important to examine the bifurcvation in this equation. the authors considered the forced Rayleigh oscillator containing a diode. By considering the limit α → ∞ for a parameter α contained in the system, the ideal diode constrained equation is defined. Then, the rigorous analysis of the bifurcation phenomenon is made for the forced Rayleigh oscillator.

This paper considers the forced Rayleigh oscillator containinig a large parameter α and shows that the bifurcation concerning the chaos generated in the oscillator can be accounted for by the ideal diode constrained equation by constructing and comparing the detailed bifurcation diagrams for the two systems.
An algorithm tracing out the tangent bifurcation curves and its application to duffing's equation
Authors: Kitajima Hiroyuki , Kawakami Hiroshi
Published: July 2007

The bifurcation diagram is constructed in the analysis of the bifurcation phenomenon. A problem in the conventional method of bifurcation diagram construction is that the computation is interrupted at the cusp point on the tangent bifurcation curve. Consequently, it has been necessary to determine the bifurcation set independently, excluding the cusp point, and then connect the curves afterward. This increases the time for constructing the bifurcation diagram when there exists a cusp point. Especially, when there exist multiple cusp points in the range where the parameter takes a small value, it has been almost impossible to trace the bifurcation curve.

From such a viewpoint, this paper proposes an algorithm based on the concept of the vector field, where the tangent bifurcation curve can be determined as a continuous curve, even if cusp points are included. the proposed algorithm is applied to the Duffing equation, and the result of computation is shown when the tangent bifurcation set including multiple cusp points is traced.
“Individually normalized” least mean square algorithm suitable for fixed‐point processing and its application to active noise control
Authors: Fujii Kensaku , Ohga Juro
Published: July 2007

By the fixed‐point procesing, a cheap and fast processor can be obtained which is an effective approach in reducing the production cost. In the adaptive filter, where the coefficient correction which is calculated in each sampling period to be added to the filter coefficient, the adjustment of the filter coefficient is made impossible if the coefficient correction is less than the minimum value that can be represented by the fixed‐point representation.

In the normalized least mean sqaure (NLMS) algorithm, the normalization using the norm is applied, which increases the probability that the coefficient correcton is less than the minimum value. This problem is solved by extracting the coefficient correction as the “difference between the impulse response of the unknown signal trnsmission system as the object of identification and its estimation.” In the “individually normalized” least mean square (LMS) algorithm, this difference is derived by calculating the ratio between the product‐sum of the residual response with adaptive filter output and the square‐sum of the tap output. Then, the result is normalized individually for each coefficient.

This paper then preents the stability condition which serves as the design principle of the proposed method. the parallel‐shifting integrating configuration is presented, which has the computional complexity less than that of the NLMS algorithm. the method is applied to the filtered‐x algorithm, and the usefulness is verified.
A new recursive algorithm for linear equation and its application to adaptive signal processing
Authors: Furukawa Toshihiro , Maeda Tsunenori , Kubota Hajime
Published: July 2007

The solution of a system of linear equations is very important in various fields of engineering, and various methods have been presented for the numerical solution. Especially, in the adaptive signal processing and adaptive control, the system of equations is often considered where the coefficient matrix is (pseudo‐) positive‐definite and symmetrical. the conjugate graduate method is known as a means to solve such a system of equations. Letting the rank of the coefficient matrix be R, it is a method where the solution for the system of equatins is determined by iterating a certain procedure R times. In this metho, even if the iterative process is terminated on the way due to the constraint for the computation time, for example, an approximate solution which is somewhat accurate is obtained. This method, however, still has room for improvement with respect to the accuracy of the approximate solution.

From such a viewpoint, this paper examines geometrically the iterative computation process in the conjugate gradient method and, based on that result, proposes a new method of iterative solution for the system of linear equations with symmetrical coefficient matrix. Then the original method is slightly modified and an adaptive algorithm is derived by applying the result to the parameter estimation of the adaptive filter. Those methods are based on the orthogonal projection operation from the solution to be determined to the linear space. Consequently, it is expected that, even if the iterative computation is terminated on the way, a more accurate approximate solution is obtained, compared to the case of the conjugate gradient method or the adaptive algorithm based on the conjugate gradient method. By the property of the method proposed in this paper the method is useful when the coefficient matrix is ill‐conditioned. It is expected that the method will effectively be utilized in the signal processing and control.
Approximation of group delay response of allpass filters using weighted least square method
Authors: Okuda Masahiro , Matsuyama Kojiro , Ikehara Masaaki
Published: July 2007

Allpass filters with prescribed group‐delay response are useful in compensating such response. In general, the approximation of group‐delay response is formulated as a nonlinear problem; thus, its approximation becomes difficult. the design methods with nonlinear optimization have the problem that initial values of filter coefficients are needed and heavy computation is required. the design method is simplified in the conventional method where magnitude response is approximated instead of group‐delay response, but the approximation error is increased in the indirect methods.

This paper proposes a method in which group‐delay response is approximated by a linear function and optimal solution is obtained in the least square sense by iteratively solving the linear equations. This method has the merit that the error of group‐delay response is directly evaluated. Moreover, applying Lawson's algorithm to this method, an equiripple solution can be obtained and maximum value of error can be decreased.
Improvement in stability and convergence speed on learning identification method
Authors: Fukumoto Masahiro , Kubota Hajime , Tsujii Shigeo
Published: July 2007

Learning identification is one of the most widely utilized adaptive algorithms due to its small computational complexity. A problem with this algorithm is that a division by the square norm of the state vector is included in the coefficient update process which easily produces an instability when the nonstationary signal such as speech is given as the input. A method known to cope with such a problem and to realize the stable convergence involves not updating the coefficient when small input signals continue. This paper discusses this approach. As a first step, the situation is assumed where the square norm of the state vector is less than the specified threshold and the effect of interrupting the coefficient update is analyzed. the convergence and the time‐constant are formulated and the guarantee of the estimation accuracy for the convergence value is discussed. Then, the step gain is derived for the specified guarantee value so that the convergence speed is the fastest in the stochastic sense while ensuring stability. Lastly, the effectiveness of the proposed method is verified by computer simulation. It is shown that, even if the input signal is nonstationary, the fastest convergence speed is realized, together with the satisfactory estimation accuracy, which is always obtained according to the specified guarantee value after the convergence.
Optimization of the nonlinear function of a neural net‐type filter
Authors: Arakawa Kaoru , Yamakawa Koji , Koyama Mitsuo
Published: July 2007

When a random noise is superposed on a non‐Gaussian signal with an abruptly changing component, as in the case of the image signal, it is impossible for the conventional linear filter to eliminate the noise effectively. This is one of the cases where the nonlinear filter should be applied.

This paper proposes a nonlinear digital filter based on the layered neural network, including the optimization of the nonlinear function. the proposed filter can effectively eliminate the noise by utilizing the nonlinearity of the layered neural network and its learning function. Another point is that the performance can be improved by the piecewise‐linear approximation of the nonlinear function and the automatic design of the optimal nonlinear function. the effectiveness of the proposed filter is demonstrated by eliminating the noise from the two‐dimensional image signal.
Dynamic network for identification of character locations using self‐organized clustering
Authors: Kondo Masanori , Miyanaga Yoshikazu , Tochinai Koji
Published: July 2007

This paper proposes a new network that evaluates the locations of targets, i.e., target characters, and recognizes them in an image mixed with other objects, i.e., noncharacters. This network consists of a self‐organized clustering layer, a simple perceptron layer, and a controller. The purpose of the self‐organized clustering is to evaluate the stochastic characteristics of an input data set; the self‐organization is executed by calculating the distance between stochastic characteristics in this layer and the stochastic characteristics of an input vector. The simple perceptron layer determines the location of a target character and simultaneously recognizes its character by linearly dividing all outputs given from the self‐organized clustering layer. In the proposed system, the location identification and its recognition of a target character can be adaptively performed by using two small different compensative networks. The location identification and its recognition of real target characters, which are obtained in printed boards, are also shown in this paper.
High‐speed and high‐accuracy learning using a self‐organization network and a supervised network
Authors: Miyanaga Yoshikazu , Tochinai Koji
Published: July 2007

This paper introduces a feedforward network with a new learning algorithm into which both a self‐organized mechanism and a supervised training mechanism are implemented. In particular, from some experiments, it is seen that this network can realize sophisticated signal processing and analysis data with high‐speed training ability. the network is divided into two layers, that is, a self‐organized layer and a supervised layer. However, in the self‐organized layer, the training data of the network also are used for realizing high precision. In addition, the supervised layer also is trained in order to realize quite high accuracy for data recognition. In other words, the training data are used for both layers. Accordingly, the total precision of the network is improved greatly. In addition, the high‐speed organization and the parallel processing which are embedded in the original self‐organization also are realized in the new network.

In this paper, some comparisons in which conventional neural networks, i.e., multilayer perceptron and self‐organization models, are used also are shown. In particular, as a new application of speech ARMA modelling, a new spectrum envelope estimation is explained by using this network.
Natural observation method for discrete‐time waveforms
Authors: Iwaki Mamoru , Iijima Taizo
Published: July 2007

The natural observation method provides a procedure to analyze the time‐varying characteristics of the continuous‐time waveform with mathematical rigor and can resolve the fundamental problem encountered in Fourier analysis method. In this paper, for discrete‐time waveforms a discrete natural observation method is proposed which has characteristics similar to those for the continuous natural observation method. Similar to the continuous natural observation method. Similar to the continuous natural observation theory of normal type, the discrete natural observation theory is introduced by requiring that the waveform values and the power component can be expressed in terms of sum forms. The discrete natural observation method is complete by itself as a discrete type, and not only is it similr in nature to those of the continuous type but also can be shifted naturally to the continuous type as the sampling interval vanishes.
A study of information‐presentation rate in a visual and auditory display
Authors: Kuma Hideki , Yokoi Hirokazu
Published: July 2007

This paper explores the information presentation rate in a visual and auditory display from the viewpoint of multimodal interface and carries out a comparison with that in a visual display or an auditory display. That is, using the time‐continuous model of short‐term memory, the optimum‐apportionment mode of letter presentation time, for which letters are most easily retained in shortterm memory, was determined for four subjects, when six randomly selected alphabet letters are sequentially presented in the same position on the screen and through a headset acoustically. This mode has shown the same tendency as that in a visual display or in an auditory display, but minimum presentation time has been slightly shorter than in the auditory display. the number of recalled letters in the case of presentation under the optimum‐apportionment mode is greater for all subjects than the maximum value of the number of recalled letters on condition that the presentation time of each letter is made equal. Moreover, there is a significant difference between the former and the latter. Accordingly, the effectiveness of the method employed here has been confirmed in the visual and auditory display as well. Furthermore, in the visual and auditory display, the number of recalled letters under the optimum‐apportionment mode was greater than that in the visual display or the auditory display for all subjects. In this case, significant difference was recognized for three subjects in a comparison within the visual display and for two subjects in the comparison within the auditory display.
Improved accessibility system—communication environment for the visually handicapped
Authors: Ohtake Nobuyuki , Ogawa Yasuhiko , Yonezawa Yoshimichi
Published: July 2007

The word communication in the computer science field is associated with data communication. In the original context, communication is “person‐to‐persons communication” using some language or the human voice. Nowadays, handicapped people are assisted in communication by informational equipment. the authors have developed several tools as welfare communication tools for handicapped people and related volunteers. the main theme is a support system for the visually impaired and blind. Not only is research level equipment developed, but also commercial products. In this paper, several are described, along with some problems encountered in the development of welfare communication and accessibility to handicapped people.
Memorizing and regenerating spatiotemporal patterns with a structured recurrent neural network
Authors: Li Yisheng , Miyanaga Yoshikazu , Tochinai Koji
Published: July 2007

A local connected recurrent neural network with the ability to memorize and regenerate some nonlinear complex dynamics is proposed in this paper and a new learning algorithm for this network is also developed. the network, constructed of adaptive oscillating modules, is easily applied to the realization of nonlinear dynamics. the module consists of two simple neuron nodes with recurrent connections. the new learning algorithm can independently train each module with suitable speed for given input data. the network size is also adaptively determined during the learning process. This network also has a suitable structure of a parallel VLSI system. Finally, some simulation results are given to verify the effectiveness on the proposed network structure and the learning algorithm.
Constraints‐programmed macro‐model of information selection—limits of information‐processing and the basic principle of information behavior
Authors: Nagaya Tatsuhito
Published: July 2007

Information‐related activites are strongly influenced by many constraints at the individual level: physiology, time, economics, degree of interest and memory, and feelings of overload or saturation. However, excluding research on human recognizing and perceiving abilities, no attempts have been made so far to study theoretically, comprehensively, and systematically individual‐level information activities and choices in relation to the interconnected workings of such constraints programmed in the body as “interest,” “physiology,” “time,” and “money”.

This paper first recognizes human beings as “living information‐processing systems,” and it studies mutual relations between information selection activities and the limits of human information‐processing capacity and intellectual‐physiological functions. This study is based on a “macro‐model of information selection” at the individual level. It also examines the framework for information selection and human functions for picking up information.
Human interface using surface electromyography signals
Authors: Koike Yasuharu , Kawato Mitsuo
Published: July 2007

We have been working toward the construction of a forward model arm employing a neural network model with electromyographic signals as the control input. We have succeeded in estimating 1) the joint torque during isometric contraction in a plane from the electromyographic signals, 2) the path of motion from the degree of joint acceleration as well as 3) the path of motion from the joint torque and 4) the position in three‐dimensional space. In this paper, we present a new human interface employing a model of an arm, robot control of an artifical hand, and the learning of motion capability. In addition, based on the fact that we can estimate the position of the arm in three‐dimensional space, we discuss as an example of the human interface the results of generating motion from electromyographic signals in a hypothetical arm using a neural network model.
Theoretical analysis on the allowable number of vehicles in automated guided vehicle systems
Authors: Sasaki Atsushi , Masuyama Shigeru , Yamakawa Eiki
Published: July 2007

Recently, automated guided vehicle (AGV) systems have been introduced widely into plants. In most cases, the performance the AGV system is evaluated only by simulation and other similar methods. The authors are conducting research to analyze theoretically the performance of the AGV system. As the first step toward their goal, this paper reports on the result concerning the number of vehicles that can be contained in the system.
Multivalued regularization network‐a theory of multilayer networks for learning many‐to‐h mappings
Authors: Shizawa Masahiko
Published: July 2007

The regularization network (RN) is a network for learning input‐output mapping proposed by Poggio and Girosi from the viewpoint of learning = function approximation. the RN, which is derived from the standard regularization theory, is extended to an approximation of multivalued mappings from examples to make the learning of inverse models of nonlinear systems possible. This extension is called multivalued regularization network (MVRN). the MVRN is derived based on the multivalued standard regularization theory (MVSRT), which in turn is a based on direct representation of the mulitivalued functions by using Kronecker's tensor product. In the MVRN, the learning of the weight parameters from the traning data results in simultaneous linear equations that are similar to those of conventional regularization networks. In the present theory, the clustering operations for separating training data into those correponding to single‐valued element functions are unnecessary. As with the conventional methods, the radial basis function (RBF), generalized radial basis function (GRBF), spline approximations, and Hyper‐BF networks can be extended to those of multivalued functions by specializaing MVRN or by marking the number of basis functions smaller than the number of training samples. Direct representation of the multivalued function used in the present theory has broad application as a basic equation for more general classes of networks to learn multivalued mappings.
Global optimization method using intermittency chaos
Authors: Fujita Tokumitu , Watanabe Takao , Yasuda Keiichiro , Yokoyama Ryuichi
Published: July 2007

The nonlinear global optimization methods developed so far can be divided into deterministic methods and stochastic methods. Various approaches proposed recently in which chaos, which is a probabilistic phenomenon and is generated by a deterministic dynamical system, is used to solve nonlinear global optimization problems. Chaos is used in these methods because fluctuations away from the local solution and global optimal solution can be searched without trapping into the local solution. the method of unconstrained global optimization proposed here uses intermittency chaos. In this proposed method, the time history of a discrete dynamical system containing the return map, which generates the intermittency chaos, is simulated and during convergence (nonperiodically) to the local optimal solution, the global optimal solution is searched without trapping into the local optimal solution. the validity of the proposed method is confirmed by applying it to a standard test problem.
Algorithms for computing the distances between unordered trees
Authors: Liu Shaoming , Tanaka Eiichi
Published: July 2007

This paper proposes algorithms for computing three kinds of distances between two rooted and unordered trees (R‐trees) and those between two unrooted and unordered trees (trees). Those are the distance based on the strongly structure preserving mapping (SSPD), that based on the closest common ancestor mappings (CD) and that based on the maximal closest common ancestor mapping (MCD). the time and space complexities to compute each distance between two R‐trees Ta and Tb are OT(ma Na Nb) and OS(Na Nb), respectively, and those to compute each distance between two trees Ta and Tb are OT(max(ma,mb)2 NaNb) and OS(NaNb), respectively, where ma(mb) and Na(Nb) are the largest degree of a vertex and the number of vertices of Ta(Tb), respectively. the proposed algorithms for SSPD and CD are more efficient than the algorithms previously proposed. MCD is newly proposed in this paper. Those distances can be applied to structureactivity studies in chemistry and various structure comparison problems.
A study of DCT image coding using adaptive three‐dimensional scanning
Authors: Sugiura Akihiko , Inatsu Minoru
Published: July 2007

In video bandwidth compression, motion compensation and two‐dimensional DCT have been used in a hybrid scheme. In this research, in place of the motion compensation of previous methods, a three‐dimensional DCT is investigated that uses a DCT transform to reduce the interframe redundancy. When a three‐dimensional DCT transform method is used for transmitting the DCT coefficients of video, the transmitted code rate and decoder signal‐to‐noise ratio can vary depending upon the three‐dimensional scanning method used for the DCT coefficients. These parameters are influenced by both image detail and motion. an adaptive scanning method is proposed in which the three‐dimensional scanning method is adaptively switched among four options. Simulation results show that compared to a fixed scanning method, in the adaptive approach, when all the post‐quantized coefficients are transmitted (fixed image quality), the transmitted coded rate is economized, and even for the case in which the number of DCT coefficients that is transmitted is restricted, the reduction in image quality can be made very small.
Acceleration of the steepest descent method for the real symmetric eigenvalue problem
Authors: Ozeki Takashi , Iijima Taizo
Published: July 2007

This paper discusses the eigenvalue problem for the real symmetric matrix, especially the determination of the largest eigenvalue. the largest eigenvalue is the maximum extremum of the objective function called the Rayleigh quotient and can be determined by the steepest descent method. It is known, however, that the steepest descent method suffers from slow convergence because it converges linearly. Especially, when the largest and the next largest eigenvalues have very close values, the convergence is particularly slow.

This paper analyzes this situation and shows that the convergence can be accelerated by combining the steepest descent method with a technique called shaking. Finally, it is demonstrated by a numerical example that the convergence is accelerated drastically by the proposed technique.
A study of the number of tracks required for the reconfiguration of mesh‐connected processor‐element networks
Authors: Kaneko Mineo , Tsunokawa Toshihiko , Hirota Takahiro , Onoda Mahoki
Published: July 2007

The reconfiguration technique for a processor network is among the fault‐tolerant techniques in monolithic realization of a multiprocessor network. the problem is composed of the mapping of logical processor element (PE) to physical PE and the physical realization of the logical connections. This paper considers two‐ dimensional mesh array architecture and discusses the routing mechanism (required number of tracks) to support the processor mapping based on the compensation path. the eight adjacent neighbor is considered in the processor substitution in composing the path. It is shown that four tracks for each channel between PE are sufficient under the condition of no port‐exchange and no crossover. It is also shown that, when a compensation path exists under the four adjacent neighbor substitution condition, there exists a routing mapping using at most three tracks per channel. As to the evaluation of the number of tracks, the channel‐cut in the dual relation to the routing path is introduced; this aids in both evaluation and proof.
A digital filter for restoring a stochastic signal from noisy and quanitzed level observations
Authors: Nakasako Noboru , Ohta Mitsuo
Published: July 2007

A practical and suboptimal estimation algorithm, proposed as a signal restoration method based on Bayes' theorem, resembles a previously reported method used to design a wide sense digital filter, especially for noisy and level‐quantized observations. The proposed method utilizes linear and nonlinear correlation information between the unknown acoustic signal and the observation value (before quantization operation) by using quantized level observations. The effectiveness of the proposed theory is confirmed experimentally through the simulation technique and by applying it to the actual reverberation data contaminated by a background noise.
A noise reduction method for chaotic time series
Authors: Itoh Ken‐Ichi
Published: July 2007

Intensive studies have recently been made on the noise reduction method for the chaotic time series. In those approaches, the trajectory of the attractor is reconstructed in the multidimensional space form the single‐variable time‐series data, and then the deviation of the trajectory is corrected. In the conventional method, the noise is assumed to be Gaussian distribution. Consequently, when the outliers are contained in the real data, they are difficult to delete.

This paper intends to solve this problem and proposes a noise reduction method for the chaotic timeseries data, considering not only the noise with the Gaussian distribution, but also the outliers. A method is devised that eliminates the outliers efficiently using Biweight estimation and similar methods, and a program is constructed based on the idea. the experimental data are constructed by adding the pseudorandom variable with the Cauchy or Gaussian distribution to the chaotic timeseries data generated from the Hénon map and the Lorenz model. Using these data, the noise reduction experiment is conducted; the relative error, the phase plot and correlation dimensions are examined. It is verified as a result that the proposed method can reduce drastically the effect of the outliers compared to the conventional methods, and has nearly the same noise reduction performance as in the conventional methods for the noise with the Gaussian distribution.