bluuebunny/crossref_metadata_2025_split huggingface dataset:
The analysis of nonstationary processes based on a kinetic model
Authors: Takizawa Yumi , Fukasawa Atushi , Oda Keisuke , Harashima Hiroshi 
Published: July 2007

AbstractThis paper presents a new analysis method for the nonstationary phenomenon using modeling. Method efficacy is investigated and effectiveness is demonstrated. Nonstationarity is modeled into the kinetics of the generating process. the behavior of the nonstationary process is represented by the characteristics at a point on the time axis (instantaneous characteristic) and the characteristics of its time variation (time‐variant characteristics). By estimating the nonstationary spectrum, the instantaneous characteristics are determined and then the time‐variant characteristics are analyzed by applying the kinetic model. the nonstationary phenomenon is first modeled using kinetic energy. Characteristics at a point on the time axis are regarded as a point of mass. Position, velocity, and acceleration are determined; these parameters signify a model with time‐varying characteristics. the arising time of the event is determined, based on the relations among the parameters. the characteristic plane is constructed using these parameters, and nonstationarity is evaluated on the plane. the proposed algorithm is then evaluated using an artificial signal and the model is validated using a speech signal. This analysis yields a new finding that deals with the characteristics of the phoneme, thus demonstrating the usefulness of the proposed method.
Hopfield‐type networks: Making the condition of learning pattern more lenient by threshold
Authors: Aizawa Tadashi , Hyogo Akira , Sekine Keitaro 
Published: July 2007

AbstractThe information storage algorithm of a Hopfield‐type network is a kind of self‐correlation learning. This algorithm needs the condition in which vectors of learning patterns cross at right angles to each other. This paper proposes a method to make this condition easier. To this purpose, threshold is used. An investigation of how to decide quantity is included. This paper discusses a network with units whose state is 1 or 0. Fixing method of threshold has not been proposed before to this type of network. It is, therefore, proposed in this research; the goal is to facilitate learning patterns.
Decomposition of flowcharts using a digraph hierarchical property
Authors: Kato June , Miyake Nobuhisa 
Published: July 2007

AbstractThis paper discusses the hierarchical properties of digraphs and proposes flowchart decomposition algorithms using these properties. the hierarchical structure discussed here is based on only the topological relationships between vertices and the inclusive relationship among sets of vertices. When the given flowchart represents the control flow of a computer program, this hierarchical structure also shows strong correspondence between these inclusive relationships and program modules. the proposed flowchart decomposition algorithm consists of one algorithm for detecting modules and another algorithm for further decomposing the detected modules. This paper focuses on the former algorithm.Because the hierarchical structure discussed in this paper corresponds to the traditional program modules (e.g., function or procedure) of most of the computer programming languages, the module‐detection algorithm can be used not only for decomposing flowchart but for more general purposes, including module design. Two types of module‐detection algorithm are discussed in this paper. One detects all modules, and the other detects a restricted subset of modules from the standpoint of flowchart decomposition. We then demonstrate with a practical example that the latter algorithm is ten times faster than the former.
An effective method to find all solutions of piecewise‐linear circuits by using partitioning
Authors: Mizutani Hikaru 
Published: July 2007

AbstractWith the expansion of the circuit scale in recent years, the dimension of the circuit equation to be analyzed also is increased, which requires a tremendous amount of time in the processing. In addition, the circuit often contains a large number of nonlinear elements, which may result in nonunique multiple solutions.This paper aims at the solution of such a problem and proposes an algorithm as a means to determine all solutions of the nonlinear circuit with the piecewise‐linear approximation with a high speed. In the proposed algorithm, the circuit is partitioned and each subnetwork is analyzed. In the proposed analysis, the relation is derived for each of the linear regions of the subnetwork, between the current flowing from other subnetworks at the partitioning points and the node voltages.The existence of the solution is examined for each linear region. Then the subcircuits are connected successively and the current‐voltage relation is derived for a larger subnetwork. Only the linear regions which have the possibility of containing a solution is considered in the calculation, and it is expected that the computation will be completed at a high speed.By iterating the connection process, all solutions for the circuit can eventually be obtained. Since the subcircuit contains fewer nodes and fewer linear regions, it is expected that the analysis of the subcircuit can be executed at a high speed.
Image coding and decoding by discrete‐time cellular neural networks
Authors: Ikegami Munemitsu , Tanaka Mamoru 
Published: July 2007

AbstractWhen the original signal to be encoded has a strong correlation in the neighborhood, as in the case of the natural image, it can be expected that the original signal is represented by a smaller number of bits.This paper proposes the following low‐bit coding system. the analog image is converted into the digital image by A‐D conversion in the transmitter based on the dynamics of the locally interconnected discrete‐time cellular neural network (DTCNN). the digital image is passed through a lowpass filter in the receiver so that the original analog image is restored. In this method, the coding of the static image is reduced to the optimization problem where the error between the original image and the decoded image is minimized. the distortion function is defined so that the noise generated by encoding is suppressed from the viewpoint of the whole image.A high‐quality image is reconstructed by the dynamics of the multivalued neuron, which is an extension of the output of the neuron to multiple values. In this method, a parallel processing dynamics is employed, where a complex function can be realized from simple devices, and it is expected to realize the digital conversion in real‐time of the analog information which is input in parallel, as in the case of the light input to the retina.
An extended overlap‐add method and overlap‐save method for sampling rate conversion
Authors: Muramatsu Shogo , Kiya Hitoshi 
Published: July 2007

AbstractThe overlap‐add (OLA) and overlap‐save (OLS) methods are well known as efficient schemes for higher‐order filtering. In those methods, the linear convolution for the infinite‐duration data is reduced to the circular convolution for the finite blocks, and the fast‐Fourier transform (FFT) is applied to the execution of the circular convolution.This paper proposes new OLA and OLS methods, which can directly be applied without a redundancy to the rate conversion. First, the conventional theory is extended for the finite‐duration data. Then, the result is generalized for the infinite‐duration data. Two methods are proposed as the main result in this paper, which are the extended overlap‐add and extended overlap‐save methods. Finally, the proposed method is compared to the polyphase structure, which is well known as an effective realization method for the rate conversion.
Noise reduction in state‐space digital filters using high‐order error feedback
Authors: Hinamoto Takao , Karino Shuji 
Published: July 2007

AbstractA technique for the reduction of the output noise variance in state‐space digital filters is developed using a high‐order error feedback consisting of a finite impulse response (FIR) digital filter. First, the optimal error feedback structure using all of the elements of the coefficient matrices in the FIR digital filter is derived. Next, the suboptimal error feedback structures are shown; the elements of the coefficient matrices in the FIR digital filter are constrained to be either symmetric or antisymmetric. Finally, a numerical example is given to illustrate the utility of the proposed technique.
Bounded real property of time‐delay time‐varying systems and its application to learning control
Authors: Yashiki Satoshi , Matsumoto Naoki , Endo Tetsuro , Takahashi Tohru 
Published: July 2007

AbstractLearning control is one of the effective control methods to achieve high‐speed motion and accurate positioning of mechanical systems which repeat the same motion. In this method, the control input is improved in each trial based on the error between the desired trajectory and the system output. the learning control system is stable if the error transition system defined in learning control is bounded real (BR).Kawamura et al. have shown the stability condition of the learning control for time‐invariant continuous‐time systems based on BR property. Takahashi has studied the stability of learning control in the case of time‐varying continuous‐time systems and time‐varying discrete‐time systems.This paper derives the stability condition of the learning control for time‐delay time‐varying (TDTV) systems which have not been reported so far because of its complexity. First, the sufficient condition for TDTV systems to be BR independent of delay is derived and the circuit's theoretical interpretation for the BR condition is given. Using this result, the stability condition for learning control for TDTV systems is given. the error of learning control converges to zero by increasing the number of the trials if the corresponding error transition system, which is defined from the error at thei‐th trial and error ati+ 1‐th trial in the learning control, is BR. Finally, a numerical example of the learning control for the TDTV system which satisfies the obtained stability condition is demonstrated, showing that the derived stability condition is valid.
A method of designing filter banks with alias‐free characteristics at equally spaced frequency points
Authors: Kiya Hitoshi , Yamazaki Hirotatsu , Yamada Yoji 
Published: July 2007

AbstractIt is known that the quadrature mirror filter (QMF) bank used for subband coding cannot avoid the aliasing effect for adaptive signal processing or spectral estimation, etc. A new class of filter banks is desired for these applications where the effect of aliasing should also be considered.In this paper, a new class of filter bank is reported which has alias‐free characteristics at equally spaced frequency points. This filter bank is called frequency sampling filter bank, and it consists of nonrecursive FIR filters. This paper also reports design methods for two types of the filter banks, keeping in mind the reduction in amount of calculation for practical implementation. In one method, all channel filters of the filter bank are determined by complex exponential modulation of a prototype filter. the other method determines the channel filters by cosine or sine modulation of a prototype filter. Both designs have the forementioned aliasing characteristics, and an efficient structure based on polyphase configuration is possible.
Analysis of the equilibrium states of the hopfield associative memory using the system of walsh functions
Authors: Aoki Hiroyuki 
Published: July 2007

AbstractThis paper considers the situation where the multiple state‐patterns satisfying the orthogonality condition are memorized in the Hopfield associative memory model. Also discussed is the relation between the equilibrium state produced in the associative memory model and the memorized patterns. Numerous studies have been made of the associative memory model by the statistical approach. By contrast, this study considers the problem from the algebraic standpoint, using the Walsh functional system.As the first step, a sufficient condition is derived for the associative memory model to be in the equilibrium state. Using this condition, the equilibrium states are classified into three types and the relation between the memorized pattern and the generated equilibrium state is analyzed. As applications, a method of estimating the number of equilibrium states and their state pattern from the data concerning the memorized pattern, as well as a method of making the given pattern an equilibrium state, are shown through examples. the results are obtained by the component analysis of the state of the associative memory model using the Walsh functional system. In other words, the usefulness of applying the Walsh functional system is demonstrated.
Image restoration using layered neural networks and hopfield networks
Authors: Muneyasu Mitsuji , Yamamoto Kazunari , Hinamoto Takao 
Published: July 2007

AbstractAn algorithm is developed for the restoration of an image degraded by a known two‐dimensional (2‐D) shift‐invariant point‐spread function and corrupted with white noise. A layered neural network and the Hopfield network are used for the edge detection, and the restoration and smoothing of a blurred image, respectively. In particular, a layered neural network is proposed for exact edge detection where the inputs consist of three pixel values and a local variance in a 2‐D mask. This network can detect edges and suppress the noise in an image at the same time, and its performance is adjusted by learning. Finally, some examples are given to illustrate the utility of the proposed algorithm.
Measurement and analsis methods for critical flicker frequency and observer fatigue caused by television watching
Authors: Mitsuhashi Tetsuo 
Published: July 2007

AbstractAiming at the quantitative measurement of the fatigue of the television observer, a new practical and simple method of critical flicker frequency (CFF) measurement and analysis is considered. As to the measurement, a method is considered where the CFF at the start of the measurement is used as the initial value and the relative change is measured in a short time with a high accuracy.It is verified experimentally that the measurement by the descending series of the method of limit is suitable. As to the analysis, two methods are compared. One is to normalize the average of measured values of all the observers, and the other is to normalize the measured value of each observer and then to calculate the average. It is shown as a result that the latter can represent more clearly the change of CFF. Then the effectiveness of the proposed method in the measurement of the fatigue of the television (TV) observer is examined. CFF of the actual TV image observer is measured, including the binocular three‐dimensional (3‐D) TV. As a result, it is verified statistically that CFF depends on the observation time and the image display method. the result corresponds well to the subjective evaluation of the fatigue. Thus, it is concluded that CFF can be a useful measure in assessing quantitatively the fatigue of the TV image observer, including the binocular 3‐D TV. It is expected that the image quality and the improvement effect of the observation condition can be examined quantitatively.
Linear‐phase biorthogonal wavelet function with arbitrary regularity
Authors: Yasuoka Hiromichi , Sakamoto Yuuji , Ikehara Masaaki 
Published: July 2007

AbstractThis paper proposes a method of derivation for the linear‐phase biorthogonal wavelet functions with an arbitrary regularity, based on the finite impulse response (FIR) half‐band digital filter. Within the range of the orthogonal wavelet functions at present, the Haar function is the only one that satisfies the linear‐phase property. In the image processing and other applications, the linear‐phase property is more important than the orthogonality.From such a viewpoint, the biorthogonal wavelet functions are proposed, for which the orthogonality condition can be relaxed and the linear‐phase property can be emphasized. In its derivation, however, mathematical sophistication is involved and the range of the derived function is considerably limited. With the development of the wavelet transform in recent years, it has become more important to select the base function flexibly according to the purpose of the processing and it is desired to establish a derivation method for the more general biorthogonal wavelet function with a higher degree of freedom.This paper presents a derivation method for the more general biorthogonal wavelet function with an arbitrary regularity. the method is based on the half‐band digital filter, and the flat response is added to the filter composing the wavelet function. Then the regularity condition for the function is considered, and the amplitude square‐error is used as the evaluation function. Finally, several design examples are shown for the linear‐phase wavelet function derived by the proposed method.
Classification of ultrasonic images using fuzzy reasoning and spatial smoothing effect of textural features
Authors: Mochizuki Takashi , Ito Masayasu 
Published: July 2007

AbstractThis paper discusses the method for the semiautomatic discrimination of the biological tissue and organs, based on the medial ultrasonic data. the ultrasonic image is difficult to be evaluated on the absolute basis, since multiple physical information is included simultaneously and the image is affected greatly by the individuality of the object. This method utilizes the feature parameters of the image for various tissues, and the discrimination is executed on the relative basis by comparing the feature parameters.In the past method, the general procedure is to utilize the first‐order statistics such as the average image density. In the case of a tumor in the liver, for example, there does not exist a remarkable density difference between the image of the tumor and the surrounding normal tissues, which prevents a satisfactory discrimination of the tumor and other images.This paper aims at the discrimination of tissue images with small density differences, based on the textural feature parameters (the second‐order statistics) contained in the image. However, the crisp‐like discrimination is difficult since there is an overlapping ambiguous area between the histograms of the feature parameters of the tissues. to improve the discrimination rate for the ultrasonic image, a method is proposed which utilizes the nonlinear input‐output relation of the fuzzy inference and the spatial distribution of the image to be adapted to each object. Using the data obtained from the test phantom for the ultrasonic diagnostic equipment and the biological data obtained from four subjects, the effectiveness of the proposed method is demonstrated.
Improved methods for deriving the complete weight distribution of reed‐solomon codes
Authors: Tokiwa Kin‐Ichiroh , Tanaka Hatsukazu 
Published: July 2007

AbstractThe authors previously considered the problem of deriving the complete weight distribution (CWD) of Reed‐Solomon (RS) codes and developed a formula which established the relationship between a specific codeword set and the CWD of an RS code. If this formula is used, then the CWD of an RS code can be determined by examining fewer codewords than would be required by an exhaustive search. However, subsequent investigation showed that this formula can be applied in its current form only to codes with prime length and not to codes with composite length. A new form of this formula given herein does not depend on whether the code length is prime or composite. the set of codewords that must be examined to determine the CWD of an RS code is respecified and a formula that gives the relationship between this newly specified codeword set and the CWD of an RS code is derived. It is also shown that, when the generator polynomial of an RS code does not have unity as a root, then the number of codewords that must be examined can be reduced even further.
A fuzzy dual decomposition method for large‐scale multiobjective nonlinear programming problems with block angular structure
Authors: Sakawa Masatoshi , Yano Hitoshi , Sawada Kazuya 
Published: July 2007

AbstractThis paper considers the large‐scale multiobjective nonlinear programming problem with block angular structure. A new method is proposed for deriving the compromising solution of the decisionmaker based on the fuzzy decision, considering the fuzzy goal of the decisionmaker for each objective function. the large‐scale nonlinear programming problem (original problem) for deriving the solution based on the fuzzy decision is formulated. Then, based on the dual decomposition technique introduced by Lasdon, the dual problem for the original problem is formulated.A two‐level optimization algorithm is proposed where the formulated dual problem is decomposed and the solution for the original problem is obtained by iteratively solving the subproblems. the validity of the algorithm is examined through a simple numerical example with the block angular structure.
Edge detection using markov random field models—optimization and parameter estimation by mean field annealing
Authors: Kudo Hiroyuki , Saito Tsuneo , Kawauchi Michiko 
Published: July 2007

AbstractAn edge‐detection method based on Markov random field and statistical estimation is proposed. Compound Gauss‐Markov random fields are used as the image model, and the edge‐detection problem was formulated as the maximuma posterioriprobability (MAP) estimation problem which can determine the estimated value of line process from the observed value of intensity process. the simulated annealing (SA) method and iterative conditional model (ICM) method are well known as relaxation methods for such types of problems. However, a large amount of calculations is needed in the SA method and convergence to local optimum solution is a major problem in the ICM method.This paper determines the MAP estimation solution using the method of mean field annealing (MFA), which has shown good results for the combinatorial optimization problem. Moreover, since in this method the shape and continuity of the detected edge changes with the model parameters of compound Gauss‐Markov random field, parameter estimation is an important problem.In the previous research, those parameter estimation methods have been studied where parameters determined from experience have been used or parameters are estimated using the edges traced by a human being. This paper proposes the method of automatic parameter estimation from the observed image based on the maximum likelihood (ML) criterion. Moreover, the gradient descent method and expectation maximization (EM) algorithm are used to calculate the actual ML solution.
High‐frequency compensation of frequency‐dependent negative resistance
Authors: Taki Masahiro , Hayahara Etsuro 
Published: July 2007

AbstractThe GIC filter is one of the LC simulation active filters and has the advantages that the element sensitivity is low and the higher‐order filter can easily be constructed compared to the single‐amplifier active filters. For the high‐frequency filter, however, the filter performance may be deteriorated due to the frequency dependency of the operational amplifier represented by the GB product, for example. Several compensation methods have been proposed for the single amplifier filter, while no effective method has been proposed for the GIC.From such a viewpoint, this paper proposes a compensation method for the frequency response of FDNR composed of GIC. the proposed frequency‐dependent negative resistance (FDNR) is applied to the actual filter circuit, and it is confirmed that the circuit operates almost as is predicted by the theory.