bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modular feedbacks of discrete event systems with arbitrary control patterns
Authors: Ushio Toshimitsu 
Published: July 2007

AbstractThe modular feedback design is the following method. When a control specification in a discrete event system is given by conjunction and disjunction of a finite number of predicates, a feedback is designed for each predicate, and the whole feedback is constructed by product and sum of the component feedbacks. By this design method, the state feedback can easily be reconstructed when the control specification is modified. This paper considers the model proposed by Golaszew‐ski and Ramadge, and we derive a condition under which the control invariance of the component predicates implies the control invariance of their conjunction and disjunction. Moreover, we derive a condition under which the unique existence of maximally and minimally permissive feedback for each component predicate implies that for the conjunction and disjunction. Finally, the derived result is applied to control of a manufacturing system.
An approach to channel routing problem using neural networks
Authors: Shimamoto Takashi , Sakamoto Akio 
Published: July 2007

AbstractA model for neural network was proposed by Hopfield et al., and when applied to a traveling salesperson problem, which is known to be an NP‐complete problem, good results were obtained. This neural network is a minimal value of an energy function which has a kinetic stable point. When we express constraints and objective functions of objective combinatorial problems in forms of energy functions, neural networks having the energy functions provide solutions to the problems. Thus we applied a solution due to neural networks to the channel routing problem which is known as a method for automatic routing within LSI.This paper reports an outline of a neural network and the idea of an energy function for the channel routing problem, its application as a decision problem and a simple compaction method for optimization, and several results of computer simulation.
Complex linear prediction method based on positive frequency domain
Authors: Shimamura Tetsuya , Takahashi Shin‐Ichi 
Published: July 2007

AbstractThis paper proposes a linear prediction method using the analytic signal which occupies half the bandwidth of the real signal. Consequently, the order is halved in the proposed method, thereby reducing drastically the computational complexity. The proposed method gives a stable solution for a finite word‐length operation, and the obtained reflection coefficient has a low coefficient sensitivity. These are both useful properties in the synthesis of speech.
An electronic circuit experiment on bifurcation and chaos in phase‐locked loop circuits
Authors: Endo Tetsuro , Imai Masao 
Published: July 2007

AbstractWhen a phase‐locked loop having an FM‐modulated input signal loses synchronization, the voltage‐controlled oscillator output may produce a random signal with continuous and broad spectrum. It has been proved already that the reason for this phenomenon is related to the existence of the homoclinic orbits which give rise to the so‐called horseshoe chaos.In this paper, various subharmonic solutions originating from the bifurcation of the periodic solution of 2nd type (associated with the asynchronous solution) are observed, both by an electronic circuit experiment and by a computer simulation. This confirms the results of computer‐generated bifurcation diagrams obtained previously.As a result, it has been clarified by actual experiment that the bifurcation diagrams obtained heretofore are correct, and, moreover, the period doubling cascade route to chaos and the intermittency route to chaos on the experimentally generated Poincaré map have been confirmed.
Application of numerical schemes admitting symmetries
Authors: Maeda Shigeru 
Published: July 2007

AbstractThis paper shows that when a single‐step numerical method to integrate ordinary differential equations admits some symmetries, an infinite number of numerical solutions can be obtained from a single one without a further numerical experiment. When this property is obtained, trajectories to be integrated numerically can be confined in advance, which may lead to a reduction in the number of experiments.Here, by symmetry is meant invariance of difference equations under an action of a Lie group. However, it is not necessarily easv to judge if a scheme admits a symmetry.This paper illustrates a combination of a backward Euler method and a forward one, whereby a symmetry is attached automatically to any invariant (first integral). Kepler motion is treated as an example. For this system, the integration scheme introduced here conserves three angular momenta which produce a symmetry composed of all threedimensional rotations.By means of this symmetry group, one numerical solution produces a three‐parameter solution by way of linear transformations. It is shown also that the numerical values calculated directly by the scheme and those obtained from another solution by means of a symmetry agree with each other with sufficient accuracy.
AND‐inverse detecting circuit for the combinatorial logic circuits
Authors: Tsuiki Shigeya , Haga Takahiro 
Published: July 2007

AbstractThis paper studies an error‐detecting hardware scheme for combinatorial logic circuits (herein called the coincidence scheme). Compared with the softward scheme, the hardware scheme has several merits such as: (1) simultaneous detection of the errors when they occur doing usual operations; and (2) the possibility of detecting the intermittent faults, etc.However, the detecting circuit must be sufficiently smaller than the logic circuit, because if the errors in the detecting circuit cannot be neglected, the detecting signal may be meaningless. For such a small detecting circuit, an AND‐Inverse detecting circuit is proposed which is a special case of the coincidence scheme and also a variation of the conventional Inverse scheme. The AND‐Inverse detecting circuit can be constructed only by 2 AND and 1 EXOR elements except NOT elements. Also, it can detect any stuck‐at faults at the input and/or output points. To clarify such features, we compare it with the Inverse detecting circuit from three measures such as: (1) detecting ability, (2) detecting rate, and (3) redundancy.
A solution for the shortest time path problem with time‐windows of arrival and departure time constraints
Authors: Hohzaki Ryusuke , Fujii Susumu , Sandoh Hiroakl 
Published: July 2007

AbstractThe number of automated guided vehicles (AGVs) installed in factories has been increasing annually. It is essential to avoid such interference among AGVs as deadlocks or blockages for efficient operation of many AGVs in a transfer system.This study considers the routing problem in which a certain AGV is requested to arrive at a given destination as soon as possible without any interference. This problem is formulated as a shortest time path problem with time‐windows on nodes and arcs of a transfer network. Time‐windows are constraints on the arrival and departure time of the requested AGV to avoid interference.In previous studies, time‐windows were dealt with as constraints only for the departure time. Therefore their solution algorithm cannot be applied in this problem. We propose a solution algorithm based on a branch‐and‐bound method.
A time‐varying parameter estimation of a minimum realization ARMA lattice model
Authors: Nakagaki Atsushi , Miyanaga Yoshikazu , Tochinai Koji 
Published: July 2007

AbstractThis paper proposes a time‐varying parameter estimation of a minimum realization ARMA lattice model. The model consists of four types of elementary sections. Since each elementary section has only a design parameter after normalization, its characteristics can be represented more compactly. To estimate time‐varying characteristics, several methods with the constant weighting factor have been proposed.This paper shows the limits of the methods using the constant weighting factor and proposes an estimation method with a new variable weighting factor. The new method directly weights observed signals and can arbitrarily change the weighting factor at any time.
Speaker‐independent speech recognition using a neural prediction model
Authors: Iso Ken‐Ichi , Watanabe Takao 
Published: July 2007

AbstractThis paper proposes a speech recognition system based on the pattern prediction using neural network. In the proposed system, an independent nonlinear predictor composed of a series of multilayer perceptrons (MLP) is prepared for each class which is the object of recognition. The temporal structure of the speech pattern, especially the temporal correlation structure between feature vector sequence, is represented by the nonlinear mapping between the input and the output, and is utilized as the important feature in the recognition.On the other hand, the variation of the temporal structure of the speech pattern, due to the difference of speakers and the fluctuation of the utterance, is normalized by the dynamic programming. As the training algorithm to determine the MLP parameters composing each predictor, an iterative algorithm combining the dynamic programming and the error backpropagation is proposed, together with the proof for the convergence. A speaker independent isolated digit recognition experiment is executed to examine the basic operation of the proposed system. The parameters are estimated in a satisfactory way even from a small number of training data, and it is indicated that a high recognition performance is realized.
Stability analysis of random access scheme by lyapunov function
Authors: Wang Xiangyi , Onozato Yoshikuni , Hokanishi Hisato , Noguchi Shoichi 
Published: July 2007

AbstractThe analysis of stability in the communication system is a very basic problem in the design of the system. However, the analysis is, in general, complex and difficult.This paper discusses a simple and direct method of analysis for the stability of the communication system, and the result is applied to the computer network with a random access scheme. In the stability analysis of the random access scheme, the stability of the equilibrium state and the structural stability of the system must be analyzed.To provide an integrated analysis for those problems, a method based on the Lyapunov method is proposed. The communication system is regarded as a dynamical system and the state equation is derived. Then the Lyapunov function is used to analyze the stability. ALOHA CSMA and AA/TDMA systems are considered as application examples of the proposed method, and sufficient conditions are obtained for those communication systems to be stable.
Tomographic image reconstruction from incomplete cone beam projections by the method of convex projections
Authors: Kudo Hiroyuki , Saito Tsuneo 
Published: July 2007

AbstractThis paper proposed an effective algorithm for reconstruction of 3‐D CT images from incomplete cone beam projections. The 3‐D object can be exactly reconstructed if and only if there exists at least one point source on every plane intersecting the object. When such a condition is met, the 3‐D radon transform and its subsequent inverse transform enable the recovery and reconstruction of the original object structure. If such a condition is not met, then the incomplete measurement data prevent the exact reconstruction of the object. However, the missing data can be estimated by means of projection onto convex sets (POCS) in the 3‐D radon transform domain for signal restoration. Simulation results indicate that the method proposed herein can significantly reduce the degradation of the reconstruction caused by incomplete data.
Identification of nonlinear dynamical system by piecewise‐linear system
Authors: Nakamura Akira , Hamada Nozomu 
Published: July 2007

AbstractA piecewise‐linear function is a multidimensional one that is developed from the approximation of a broken line in one dimension, and it is well used for simple representation of nonlinear systems. This paper proposes a method of nonlinear dynamical system identification using a piecewise‐linear system by input and output data. The parameter identification scheme with adaptive observers used in a linear system is applied. This method estimates unobservable state variables and identifies parameters simultaneously using a state variable filter. To derive adaptive laws that identify parameters of a piecewise‐linear system, the continuity condition of the parameters of piecewiselinear systems on the decomposition boundaries in the state space is considered.
Maximum likelihood estimation with a weibull‐superimposed‐type model and its application to failure pattern analysis of a ground device of shinkansen atc
Authors: Fukuoka Hiroshi 
Published: July 2007

AbstractThe bathtub curve has been represented as a composite curve, where the failure pattern consists of separate initial, chance and wear‐out periods. On the other hand, some electronic system is regarded as a “system composed of subsystems whose failure patterns are different from each other”. It may happen that the failure pattern of the whole device of such a system is of a bathtub type. This paper discusses failure pattern analysis, where such a situation is modeled as a “superimposed process” of nonhomogeneous Poisson processes and proposes a computational algorithm for the maximum likelihood estimation of its parameters, where the failure pattern of the subsystems follows the Weibull processes. The results of numerical experiments indicate that this method derives an accurate solution efficiently and in a stable way. As an application to the practical problem, the model is used to analyze the failure pattern of the ground device of the Shinkansen (bullet train) automatic train control system (ATC). The failure patterns of some kinds of components are revealed, which have never been analyzed due to their complexity.
A novel design of an FIR filter with a hierachical structure and its LSI implementation
Authors: Nakamura Shogo , Kawahashi Akiyoshi , Horio Yoshihiko , Kotani Makoto , Kadowaki Yukio 
Published: July 2007

AbstractThis paper describes a novel design of a linear‐phase FIR filter and its hardware. The proposed filter has a hierarchical building block structure of tapped‐cascaded lower‐order subfilters. Since this architecture can reduce the sensitivity of the rounded filter coefficients, an effective high‐speed processing of the subfilter can be performed by using adders instead of multipliers. Also, identical subfilters are arranged regularly so that the architecture is suitable for LSI implementation. Another important feature is that the design of the higher‐order FIR filter can be replaced with that of the lower‐order subfilter. An LSI implementation of about a 45‐order FIR filter also is described.
Visualization of the three‐dimensional structure of absorbed power of electromagnetic waves–a synthetic paste phantom containing a nonionic surface active agent and measurement of its physical properties
Authors: Miyakawa Michio , Yamaura Itsuo 
Published: July 2007

AbstractThis paper considers the means of research for the biological effect on electromagnetic irradiation such as the electromagnetic environmental problem. The physical model for the biological system, i.e., phantom, together with the quantitative knowledge about its construction, is described.A function of the phantom is that it can visualize in a three‐dimensional way, the region where the temperature exceeded a certain value. The phantom has electrical constants similar to those of the biological system with known physical (electrical and thermal) properties. For this purpose, the phantom composed of the synthetic paste is considered. It has the property that the material becomes white and opeque due to the segregation of the surface active agent when the temperature exceeds a certain level.The electrical and thermal properties of the material are measured. A quantitative evaluation is made of the density of the added material in the construction of the tissue‐equivalent phantom, as well as the dependencies of physical properties on the added salt.A method of constructing the phantom according to the purpose and application is described. As a result of a series of measurements, it is demonstrated that the biological phantom of any shape with the tissue‐equivalent electrical and thermal properties, can be realized for any frequency by the commercial paste plus salt.
An area‐minimum synthesis method based on topology decomposition of multistage complex MOS gates
Authors: Dai Zhi‐Jian , Asada Kunihiro 
Published: July 2007

AbstractThis paper combines a new topology decomposition method of multistage MOS complex gates and the optimization technique for the transistor size. A method of automatic synthesis for the optimal circuit topology and the transistor size is proposed for a set of given finite topologies and for the given load capacitance and the maximum specified delay time.The procedure starts from the single‐stage complex logic circuit which is synthesized by the circuit synthesis program MoSyn [1]. By iterating the process called “cut,” the multistage circuit is constructed while restricting the number of transistors on the conduction path at the transistor circuit‐level. Then, the transistor size in the circuit is optimized for the several obtained multistage circuits using the two‐stage transistor size optimization method (MoSiz) [2, 3]. The area occupied by each circuit is evaluated.Finally, the circuit with the smallest circuit area is selected as the optimal solution. Circuit designs are actually attempted for several examples. Compared to the worst‐case circuit under the same load and delay conditions, the area is improved by 10 to 80 percent. It is verified that the optimal circuit topology depends on the given load capacitance and delay time.
Recursive least‐square algorithm with ud factorization by fixed‐point arithmetic
Authors: Tsubokawa Hiroshi , Tsujii Shigeo , Kubota Hajime 
Published: July 2007

AbstractIt is known that a recursive least‐square (RLS) algorithm with UD factorization equivalent to the (standard) RLS algorithm can be realized by using the systolic array proposed by Kung. In general, in constructing a special hardware, the wordlength of a processor is related to the arithmetic processing speed and the area of the hardware. Therefore, an important subject is how to shorten the wordlength of processors used in the systolic array executing the RLS method with UD factorization.The authors have already carried out an operational error analysis in finite wordlength floating‐point arithmetic and described that this algorithm can be executed with short arithmetic wordlength. If the algorithm can be executed with short arithmetic wordlength also in the fixed‐point arithmetic, then we can expect improved operational processing speed and simpler hardware structure compared to the special hardware of the floating‐point arithmetic mode.Thus, this paper describes an RLS method by finite wordlength fixed‐point arithmetic with UD factorization and evaluates the operational error. Then the evaluation of convergence values and number of updates of the algorithm are shown analytically. Finally, the appropriateness of theoretical analysis results of convergence values and the number of updates are confirmed by computer simulations.
Proposal of chaotic steepest descent method for neural networks and analysis of their dynamics
Authors: Tani Jun 
Published: July 2007

AbstractMost of the neural network models based on the Lyapunov stability contain various problems such as the trap of the local minimum, and the limit of their dynamic performances has been pointed out.This paper attempts to provide a new dynamic performance to such a neural network model by introducing chaos dynamics. The features of the chaotic dynamic model proposed here is that the dynamical equation describing the trajectory on the energy curve has a periodically varying nonlinear resistance in the dissipation term. By iterating the stable and unstable phases, the chaotic transitions of the state can be realized.The proposed dynamic model is applied to the error backpropagation learning and the memory recall in the Hopfield‐type network, and the chaotic minimum transitions in the dynamic process are verified, it is verified further that the intermittent chaos generated by an appropriate parameter manipulation can introduce useful dynamic behaviors into the network, e.g., the flexible learning and the memory recall with a structure containing both stability and plasticity.
Convergence properties of numerical simulation for neural networks
Authors: Urahama Kiichi 
Published: July 2007

AbstractThis paper discusses the convergence of the numerical solution of the neural network, whose stability is such that any trajectory asymptotically approaches the equilibrium solution. It is shown first that when the connection among neurons is weak, the upper limit of the step width, for which the asynchronous iteration converges, is the same as in the synchronous iteration. It is pointed out that the asynchronous method is expected to achieve a faster convergence in the parallel computer. On the other hand, when the synaptic connection is symmetrical, the asynchronous iteration does not converge in general unless the step width is set smaller than that of the synchronous iteration.It is shown also that the stiffness of the Hopfield network to solve the combinational optimization problem is enhanced with the increase of the network scale. Since the computational complexity is expected to increase rapidly in the forward Euler method, the iterative method based on the backward Euler method is proposed. It is shown that the proposed method has a better convergence property.Finally, the foregoing theoretical results are verified qualitatively through simple examples.
Neural network using oscillators
Authors: Endo Tetsuro , Takeyama Kazuhiro 
Published: July 2007

AbstractThis paper proposes an oscillator neural network which replaces the sigmoidal nonlinearities in a Hopfield neural network with oscillators. When oscillators are used as saturating nonlinearities and their rise and fall times are utilized, results similar to simulated annealing are obtained, and therefore the desired solution can be obtained in a relatively short time. As examples, we show that the 4‐bit A/D converter problem, the 10‐city traveling salesman problem, and a simple associative memory problem can be solved by the oscillator neural network.
Circuit module placement method to minimize manhattan wire length
Authors: Kasai Masahiro , Yamada Shoichiro 
Published: July 2007

AbstractIn the automatic layout design of LSI, the placement method based on Newton's method is known to produce relatively satisfactory results as the minimization of the wiring length for the module. However, a problem in this placement method is that the evaluation function must be differentiated and the total wiring length including the absolute‐value function cannot be used directly as the evaluation function. Because of this problem, the square‐sum of the wiring lengths has been used as the evaluation function instead of the sum of the wiring lengths.This paper examines first the optimal solution for the small‐scale placement problem and points out that the sum of the wiring lengths should be used as the object of minimization. Then the absolute‐value function contained in the expression for the sum of wiring lengths is approximated by the differentiable function, and a method is proposed which directly minimizes the total wiring length by Newton's method. Finally, the proposed method is applied to various placement problems and the results are presented, thus verifying the usefulness of the method.