bluuebunny/crossref_metadata_2025_split huggingface dataset:
An algorithm for generating low autocorrelation‐sidelobe skew symmetric binary sequences based on complex exponential functions
Authors: Ohue Kenji , Aibara Tsunehiro 
Published: July 2007

AbstractIn the smearing process to suppress impulse noises and the pulse compression in long‐range radar, it is crucial to employ the finite binary sequence which minimizes the sidelobe of the autocorrelation function.This paper proposes a new generation algorithm for the finite binary sequence with a sharp autocorrelation function. The method is based on the fact that the autocorrelation function θ(n) of skew‐symmetric sequence is always zero when n is odd, and the Fourier expansion coefficient sequence of the complex exponential function is an uncorrelated sequence.First, the generating function is derived for the skew‐symmetric real‐valued sequence, for which the Fourier expansion coefficient sequence is an uncorrelated sequence. An algorithm is presented in detail, where the foregoing real‐valued sequence is quantized into a binary sequence, and the binary sequence minimizing the autocorrelation is derived with the finite delay coefficients of the generating function as the variables.In the past, no generation algorithm has been found which can derive the optimal skew‐symmetric binary sequence. It is shown that the proposed generation algorithm can derive all of the optimal skew‐symmetric binary sequence derived by Golay using the exhaustive method. It is shown also that all Barker sequences with off length can be derived.
A method for numerical analysis of bifurcation of periodic solutions in nonautonomous systems with hysteretic elements
Authors: Matsuo Tetsuji , Kishima Akira 
Published: July 2007

AbstractThis paper proposes a method for a numerical analysis of the bifurcation in the nonautonomous system containing hysteretic elements. Previously, the authors discussed the case where the characteristics of the hysteretic elements can be represented by Preisach's model, and proposed a method for steady‐state analysis of the nonautonomous system containing hysteretic elements.First, a method is presented to investigate the change of the steady‐state behavior with the variation of the system parameters by combining the proposed method and the continuation method. Then another method is presented in which the singular point on the characteristic curve (solution curve) is determined using the previously derived variational equations of the system. Finally, examples of analysis by the newly proposed method are presented, and the effects of the hysteresis loss and the ohmic loss on the bifurcation are compared. A remarkable difference between the two is indicated.
Influence of time constant on coefficients estimation error derived from a lowpass filter expression for learning identification algorithm
Authors: Fujii Kensaku , Sakai Yoshihiro , Ohga Juro 
Published: July 2007

AbstractThis paper shows that the learning identification (the normalized LMS) algorithm can be expressed by a first‐order IIR low‐pass filter having rapidly varying coefficients as a function of output signal to be sent to an unknown system to be estimated. Based on the expression, this paper studies the estimation error of adaptive filters obtained by the learning identification algorithm. It is pointed out that the mean of estimation error given by the conventional analysis corresponds to the output fluctuation which can be computed by replacing varying coefficients of the lowpass filter with its arithmetic mean. However, the output fluctuation is affected by the time constant specified by the coefficients of the lowpass filter and it has a characteristic that it increases rapidly when time constant is short and decreases slowly when it is long. This means that the actual estimation error becomes larger than the result given by the conventional analysis.According to the analysis shown in this paper, it can be seen that the estimation error consists of elements for which the portion increased by the effect of time constant become fewer anti‐proportionally to the number of the tap, and those elements which increase at a constant rate independently of the number of the tap. It was shown also by simulation using white noise that the difference between the estimation error obtained in actual estimation operation which occurs when the number of the tap is small and the result given by the conventional analysis can be explained well by the analysis by simulation using white noise.
A design method of 3‐D fir digital filters detecting linear trajectory signals using the rotation and interpolation in the signal domain
Authors: Kondo Katsuya , Sugii Yasuyuki , Hamada Nozomu , Xue Pei Ding 
Published: July 2007

AbstractThis paper proposes a method for designing an FIR digital filter which extracts an object moving in a fixed direction at a fixed speed on a plane (linear trajectory signal) with some margins concerning direction and speed independently. Signals to be considered are 3‐D signals on the 2‐D space‐time coordinates.The method herein enables processing by FIR‐type prototype filter of cubic‐symmetric characteristics by rotating signal data and designing a prototype filter in the digital domain directly. Since this design method is not based on optimization design such as an iterative algorithm but finds filter coefficients in an analytical manner, the computation time is extremely short. In addition, since it is a direct design in the digital domain, it does not require s‐z transformation such as bilinear transformation and thus it is not affected by distortion caused by it. Moreover, because of the FIR type its feature is that we do not need to consider a stability check or phase distortion.
A distance measure for speech recognition based on an FM‐neuron model
Authors: Aikawa Kiyoaki , Furui Sadaoki 
Published: July 2007

AbstractThis paper discusses the speech recognition based on the time course of the local peak of the spectrum such as the formant, which has been considered important in the phoneme perception. A measure for the dynamical behavior of the spectrum is proposed based on the functional model of the FM‐neuron which is shown to exist in auditory physiology.First, the FM‐neuron is modeled as a time‐frequency filter for the spectral time‐series which responds only to the shift of the local peak frequency of the spectrum with the discrimination function for the shift direction. Then the measure to represent the difference of the output from the FM‐neuron model is derived based on the cepstral expansion of the spectrum. The measure is called the spectral movement similarity.It is shown that the spectral movement similarity on the auditory nonlinear frequency axis can be realized equivalently by the frequency weighting. A spoken word recognition experiment is conducted employing the dynamic time warping (DTW) using the spectral movement similarity. It is shown also that the recognition error is reduced greatly by combining the proposed measure and the traditional spectral distance compared to the case where only the traditional spectral distance is used. This improvement is more remarkable when the cepstral distance is used as the spectral distance, with the recognition error being reduced to one‐fourth.
A periodically time‐varying digital filter containing a discrete fourier transformer
Authors: Min Xiong Wei , Ishii Rokuya 
Published: July 2007

AbstractSo far, three periodically time‐varying models have been proposed in the research on periodically time‐varying digital filters. They are the coefficients time‐varying model, the output sampling polyphase model, and the input sampling polyphase model. Analyses of these models have also been completed by the authors.This paper proposes new models to solve a problem which the three conventional models cannot solve. It is known that a periodically time‐varying digital filter can be used to implement a spectrum scrambler. However, when these models are to be used to implement a spectrum scrambler, time‐invariant filters in these models are restricted to FIR filters.This paper proposes and analyzes an output sampling polyphase model and an input sampling polyphase model, both of which contain a discrete Fourier transformer. Relationships between the newly proposed models and the conventional coefficients time‐varying model are established.By making use of the newly proposed periodically time‐varying models, we can design a spectrum scrambler employing not only FIR time‐invariant filters but IIR time‐invariant filters as well. Furthermore, compared to the conventional models, the newly proposed periodically time‐varying models are shown to have an advantage of less amount of computation when they are used to implement a spectrum scrambler.
Optimum linear filter of PPM receiver
Authors: Inoue Tadaaki , Iritani Tadamitsu , Kinouchi Yohsuke 
Published: July 2007

AbstractThis paper considers the problem of an optimum linear filter on the receiving side of the PPM transmission system in which both the additive noise and the signal‐dependent noise exist. The optimum filter for the PPM transmission derived in this paper is the one in which the mean‐square value (MSE) of the timing error is minimized at the location of the pulse detection. In contrast to the optimum filter in the PAM transmission which maximizes the signal‐to‐noise ratio in the amplitude direction, the present optimum filter is of a different type which maximizes this ratio in the time‐axis direction.In this paper, the general equation which the optimum filter must satisfy is derived as an equation containing the previous research results. Subsequently, the timing error, optimum pulse detection level and the configurations of the filter on the receiving side and of the pulse location detector are presented. It is pointed out that, by the use of the optimum filter derived in this paper, baseband multiplexed transmission systems using pulses can be realized easily by combining the PAM and PPM systems. The method for multiplexing and the receiver configuration are shown.
Improving the efficiency of interval analysis by Kevorkian's decomposition technique
Authors: Yamamura Kiyotaka , Ushida Akio , Horiuchi Kazuo 
Published: July 2007

AbstractThe algorithm of interval analysis proposed by Krawczyk, Moore, and Jones (henceforth called the Krawczyk algorithm) is a well‐known algorithm for finding all solutions of nonlinear equations. In this algorithm, the initial region (which is given by ann‐dimensional rectangle) is divided into small subregions, and the existence of a solution in each subregion is examined. Therefore, it can find all solutions. However, the computation time of the Krawczyk algorithm grows exponentially with the dimension, hence it is not a practical algorithm for large‐scale problems although high‐speed computers are used.In this paper, Kevorkian's method is introduced to the Krawczyk algorithm to improve the computational efficiency. Kevorkian's method is a decomposition method for nonlinear equations. It reduces large‐scale nonlinear equations with sparse Jacobians into smaller equations. By this reduction, the computational efficiency of the Krawczyk algorithm is improved substantially.First, a new algorithm of interval analysis is proposed in which Kevorkian's method is introduced to the Krawczyk algorithm. Then a new permutation algorithm (algorithm for decomposing nonlinear equations) that makes the interval arithmetic well defined is proposed. The effectiveness of the proposed algorithm also is verified by numerical examples.
Realization of multirate digital filters with powers‐of‐two coefficients
Authors: Todaka Chiaki , Kambayashi Noriyoshi 
Published: July 2007

AbstractWith a view to reducing the amount of hardware in the lowpass filter (LPF), bandpass filter (BPF), and band‐elimination filter (BEF) processing important in digital signal processing, this paper presents a method for configuration of the multirate digital filters with powers‐of‐two coefficients only. The proposed filters are constructed with the sampling rate increaser, the reference LPF and the sampling rate decreaser. The reference LPF consists of the stopband‐forming filter and the pass‐band compensating filter. The stopband‐forming filter consists of a cascade of RRSs while the linear phase FIR or IIR configuration is used for the passband‐compensating filter.First, a method of configuration is presented for the reference LPF based on the sampling rate increaser with powers‐of‐two coefficients. Next, it is shown that the multirate LPF, HPF (high‐pass filter), BPF and BEF with an arbitrary cutoff frequency can be constructed easily from the reference LPF. The present method is particularly effective for narrowband LPF and HPF. Since no multiplier is used, they have zero coefficient sensitivity. It is shown by means of a design example that the present method is effective in reducing the amount of hardware.
Analysis of periodic oscillations with computer algebra
Authors: Fujisaka Hisato , Sato Chikara 
Published: July 2007

AbstractIn analyzing differential equations, computer algebra or symbolic computation is useful when we want to know the relation between the solutions and the parameters at the point near bifurcation.The object of this paper is to show the fast computation method by means of computer algebra in analyzing the bifurcation problem from the steady state to the periodic oscillatory state. The proposed method of analysis depends on Lyapunov‐Schmidt method. Instead of using trigonometric multiplication and sum formula in computation of nonlinear terms and their harmonics, both the basis vectors with polynomials in components and their inner products are utilized to reduce the computation time significantly.The example of a second‐order Van der Pol equation and the example of the higher‐order coupled system are used to give the bifurcation equation. Thus, the relation between the amplitude of oscillation and the parameter is given with the stability condition. By the proposed method with the aid of a microcomputer and symbolic computation language of interpreter type, the computation time is shorter.
Effects of respiration on heart‐rate variability measures
Authors: Murata Atsuo 
Published: July 2007

AbstractThere are many studies that measure the mental workload or evaluate the autonomous nervous function by heart‐rate variability measures. Heart‐rate variability is influenced not only by the stress or the workload but also by respiration. Therefore, it is important to clarify the effects of respiration on heart‐rate variability measures.This paper discusses the effects of the respiration frequency, the depth of respiration and the dispersion of the respiration interval on heart‐rate variability. It was shown that the number of peak and trough waves in the time series of R‐R intervals was influenced by the respiration frequency. Moreover, the measures obtained by the power spectral analysis of R‐R intervals were found to be influenced considerably by the respiration frequency. The heart‐rate variability measures tended to increase with deep respiration. The effects of the dispersion of respiration intervals on heart‐rate variability measures were not so remarkable.
Theory on extended form of interpolatory approximation of multidimensional waves
Authors: Kida Takuro , Yoshioka Leopoldo Rideki , Takahashi Sadayoshi , Kaneda Hajime 
Published: July 2007

AbstractThis paper presents a comprehensive discussion of the approximation of then‐dimensional wavef(X) using the sampled values of the output wave obtained by exciting a series of time‐invariant linear circuits by the wavef(X). It is assumed that the approximate waveh(X) off(X) is given by the sum of sample values of the output wave multiplied by certainn‐dimensional waves. For simplicity,n‐dimensional waves to be multiplied with the sample values are called the interpolation functions.The set of sample points treated in this paper is defined as a subset obtained by sampling periodically the vertices of then‐dimensional parallelepipeds placed periodically in the spaceRn.Such a set of sampling points includes the most of the typical arrangements of the sampling points, such as the hexagonal and the octagonal lattices on the two‐dimensional space.It is assumed that the sample values contain statistically independent errors such as the observation error and/or the quantization error. Moreover, it is assumed that the interpolation functions have the supports which are parallel‐translations of each other.First, it is assumed that the functional forms of these interpolation functions may be different. Further, a set ofn‐dimensional waves is considered where the corresponding spectrum has the weightedp‐norms smaller than the prescribed positive constant. The standard deviations of the difference betweenf(X) and their approximations are considered. As the measure of the approximation error, the upper limit of the standard deviation obtained by varying the original waves over the given set of waves is adopted.In the following sections it is shown that the interpolation functions minimizing the forementioned measure of error can be expressed as the parallel‐translations of a finite number of functions. Further, in special cases, the interpolation functions have the discrete orthogonality. Since the measure of error is a convex function of the interpolation functions, it is ensured that the global optimum is obtained easily by using the ordinary numerical optimization. For some special cases, the concrete expression for the optimal interpolation functions are derived. Considering the approximation system in the reverse direction, where the linear circuits first passing the input wave are exchanged with the interpolation filters, it is shown that the new interpolation functions also minimize the same measure of error. As a direct consequence, a successive approximation of the interpolation functions is presented, which is suited to the applications such as the multiplex communication of the images of both directions.
A simple method for precise estimation of sinusoidal frequency
Authors: Noro Yuichi , Inomoto Kenji , Kuno Kazuhiro 
Published: July 2007

AbstractThis paper proposes a method for precisely estimating sinusoidal frequency using five samples. The estimation procedure is implemented by interpolating the impulse location between DFT results. Five samples are used because two complex components are available in the DFT results. However, an estimation method which uses four samples and is called Prony's approximation method is known in the literature. To derive interpolation formulas for six or more samples is more complex. In this paper, strict estimation formulas and their simplified versions are deduced from the DFTs of five samples. The frequency estimation error is also discussed with a computer‐simulated experiment which shows a 1 percent r.m.s. error at a signal‐to‐noise ratio of 30 dB. This method may be applicable for representing frequency in a direct binary form which can be processed by simple operations such as addition, exclusive‐OR, and sign extractions form the calculated value.
An algorithm for embedding a biconnected planar graph to maximize the total sum of vertex‐ and edge‐weights on the exterior window
Authors: Kotani Ken , Masuda Sumio , Kashiwabara Toshinobu 
Published: July 2007

AbstractSuppose that a biconnected planar graph G = (V, E) is given such that each vertex and edge are weighted. This paper proposes an algorithm for finding a planar embedding such that the total sum of weights of vertices and edges on the exterior window is maximized (among all possible planar embeddings of G. Among algorithm for determining planarity of a graph there is one that uses a data structure called a PQ tree. The algorithm presented in this paper is the one which extends it and uses the PQ tree as its data structure as well. However, it can find a required planar embedding in O(|V|) time by assigning special weights to each node of each PQ tree generated in the algorithm.
An algorithm for testing the planarity of a hierarchical graph
Authors: Kashiwabara Toshinobu , Masuda Sumio 
Published: July 2007

AbstractSuppose that a graph G = (V, E) and a partition V1, V2, …, Vk (where Vi ∩ Vj = ϕ(i≠j), V1 ∪ V2 ∪ … ∪ Vk = V) of V into K subsets are given. If a vertex v belongs to a set Vi, the level of v is said to be i.This paper proposes an algorithm which tests whether or not there is a planar embedding of G satisfying the following two conditions.Condition 1. The vertices are arranged from top to bottom in the increasing order of their level (the vertices of the same level are placed on one horizontal line).Condition 2. An edge crosses a horizontal line at most at one point. This algorithm uses a data structure called the PQ‐tree and it can be executed in O(|V|) time.
Fault tree analysis using disjoint disjunctive forms
Authors: Tajima Hisaaki , Iida Toshiyuki 
Published: July 2007

AbstractIn fault tree analysis (FTA) using minimal cut sets, the analysis time increases exponentially with fault tree size, thus analyzing a large fault tree is tedious. This paper proposes some algorithms to efficiently calculate the failure rate and structural importance of fault trees. Each fault tree is decomposed into subtrees, whose disjoint disjunctive forms are derived. The failure rate of the top event can be calculated with these disjoint disjunctive forms. Some examples confirm the efficiency of these algorithms.
The cooperative behavior of a compound system
Authors: Hirai Kazumasa , Shindou Hisanori 
Published: July 2007

AbstractThe behavior of a compound system made up of several subsystems may display a certain order due to the cooperation of each of the subsystems. The heart, made up of many different cells, is an example of such a system. When not connected to each other, the cells behave independently; but when connected, they cooperate to produce order in the total system.The purpose of this paper is to investigate the transient behavior of each subsystem, and its contribution to the steady state in such a cooperative system. In order to investigate this, a multi‐inverted pendulum system will be studied, in which several inverted pendula attached to a small cart are controlled in such a way that they will stand inverted when the cart is moving. The results of this simulation produce an interesting motion which might not be logically deduced otherwise.
Algorithms for detecting separability of nonlinear mappings using computational graphs
Authors: Yamamura Kiyotaka , Kiyoi Masahiro 
Published: July 2007

AbstractA nonlinear mapping is called separable (or partially separable) if it contains all (or some) variables in the separable form. Separability is a very valuable property of nonlinear mappings. Recently, many algorithms have been presented that exploit the separability of nonlinear mappings for improving the computational efficiency. It has been shown that the substantial improvement of computational efficiency can be achieved by exploiting the separability, especially when the number of separable variables is large.To apply these algorithms, it is necessary to detect which variable is contained in the separable form. However, such algorithms have not been presented in the past. When the nonlinear mapping is large scale and complicated, it is difficult to detect the separability by inspection.In this paper, some algorithms are proposed that detect the separability of nonlinear mappings automatically. For this purpose, the concept of computational graphs is introduced. Two algorithms are proposed that are based on the top‐down search and the bottom‐up search.These algorithms are the combinations of simple techniques, but they can detect the separability in execution time proportional to the number of edges of the computational graph.