A new algorithm, which is incorporated into the waveform relaxation analysis, for efficiently simulating the transient response of single lossy transmission lines or lossy coupled multiconductor transmission lines, terminated with arbitrary networks will be presented. This method exploits the inherent delay present in a transmission line for achieving simulation efficiency equivalent to obtaining converged waveforms with a single iteration by the conventional iterative waveform relaxation approach. To this end we propose 'line delay window partitioning' algorithm in which the simulation interval is divided into sequential windows of duration equal to the transmission line delay. This window scheme enables the computation of the reflected voltage waveforms accurately, ahead of simulation, in each window. It should be noted that the present window partitioning scheme is different from the existing window techniques which are aimed at exploiting the non–uniform convergence in different windows. In contrast, the present window technique is equivalent to achieving uniform convergence in all the windows with a single iteration. In addition our method eliminates the need to simulate the transmission line delay by the application of Branin's classical method of characteristics. Further, we describe a simple and efficient method to compute the attenuated waveforms using a particular form of lumped element model of attenuation function. Simulation examples of both single and coupled lines terminated with linear and nonlinear elements will be presented. Comparison indicates that the present method is several times faster than the previous waveform relaxation method and its accuracy is verified by the circuit simulator PSpice.

We report on an experimental hysteresis in the Hopfield networks and examine the effect of the hysteresis on some important characteristics of the Hopfield networks. The detail mathematic description of the hysteresis phenomenon in the Hopfield networks is given. It suggests that the hysteresis results from fully–connected interconnection of the Hopfield networks and the hysteresis tends to makes the Hopfield networks difficult to reach the global minimum. This paper presents a T–Model network approach to overcoming the hysteresis phenomenon by employing a half–connected interconnection. As a result, there is no hysteresis phenomenon found in the T–Model networks. Theoretical analysis of the T–Model networks is also given. The hysteresis phenomenon in the Hopfield and the T–Model networks is illustrated through experiments and simulations. The experiments agree with the theoretical analysis very well.

This paper proposes a new class of unidirectional byte error locating codes, called single symmetric bit error correcting and single unidirectional byte error locating codes, or SEC–SUbEL codes. Here, "byte" denotes a cluster of b bits, where b2. First, the necessary and sufficient conditions of the codes are clarified, and then code construction method is demonstrated. The lower bound on check bit length of the SEC–SUbEL codes is derived. Based on this, the proposed codes are shown to be very efficient in some range of the information length. The code design concept presented for the SEC–SUbEL codes induces the generalized unidirectional byte error locating codes with single symmetric bit error correction capability.

Synchronization has been one of the problems in M–ary spread spectrum communication systems. In this letter, we propose the frame synchronization method using the Hadamard matrix and a frame synchronization method of PCM communication systems. Moreover, we analyze the probabilities of keeping synchronous state and frame renewal rates, and we evaluate the relationship between these probabilities and the number of stages of counters.

This paper proposes a methodology for fine evaluation of the uncertain behaviors of systems affected by any fluctuation of internal structures and internal parameters, by the use of a new concept on the fuzzy mapping. For a uniformly convex real Banach space X and Y, a fuzzy mapping G is introduced as the operator by which we can define a bounded closed compact fuzzy set G(x,y) for any (x,y)∈X×Y. An original system is represented by a completely continuous operator f defined on X, for instance, in a form xλ(f(x)) by a continuous operator λ: YX. The nondeterministic fluctuations induced into the original system are represented by a generalized form of the fuzzy mapping equation xGβ (x,f(x)) {ζX|µG(x,f(x))(ζ)β}, in order to give a fine evaluation of the solutions with respect to an arbitrarily–specified β–level. By establishing a useful fixed point theorem, the existence and evaluation problems of the "β–level-likely" solutions are discussed for this fuzzy mapping equaion. The theory developed here for the fluctuation problems is applied to the fine estimation of not only the uncertain behaviors of system–fluctuations but also the validity of system–models and -simulations with uncertain properties.

We introduce recurrent networks that are able to learn chaotic maps, and investigate whether the neural models also capture the dynamical invariants (Correlation Dimension, largest Lyapunov exponent) of chaotic time series. We show that the dynamical invariants can be learned already by feedforward neural networks, but that recurrent learning improves the dynamical modeling of the time series. We discover a novel type of overtraining which corresponds to the forgetting of the largest Lyapunov exponent during learning and call this phenomenon dynamical overtraining. Furthermore, we introduce a penalty term that involves a dynamical invariant of the network and avoids dynamical overtraining. As examples we use the Hnon map, the logistic map and a real world chaotic series that correspond to the concentration of one of the chemicals as a function of time in experiments on the Belousov–Zhabotinskii reaction in a well–stirred flow reactor.

We propose two methods to fuse auditory information and visual information for accurate sppech recognition. The first method fuses two kinds of information by using linear combination after calculating two kinds of probabilities by HMM for each word. The second method fuses two kinds of information by using the histogram which expresses the correlation of them. We have performed experiments comparing the proposed methods with the conventional method and confirmed the validity of the proposed methods.

This paper describes a segmentation method of liver structure from abdominal CT images using a three–layered neural network (NN). Before the NN segmentation, preprocessing is employed to locally enhance the contrast of the region of interest. Postprocessing is also automatically applied after the NN segmentation in order to remove the unwanted spots and smooth the detected boundary. To evaluate the performance of the proposed method, the NN–determined boundaries are compared with those traced by two highly trained surgeons. Our preliminary results show that the proposed method has potential utility in automatic segmentation of liver structure and other organs in the human body.

An optimal control theory has been applied to a biological compartment system to show a method to analyze the control principle of biological system represented by compartments. Present theory has been proposed to afford a theoretical back ground and validity for the strategy of drug administration or control of the anesthetic agent in practical medicine. The instantaneous change of the concentration of a given material within a biological system has been expressed by differential equations. Each compartment has been set to be transferred a material from all other compartments and conversely each compartment sends it to all other compartments. The control input was restricted to be one kind. The performance function involved the deviation from the target value, the rate of change in concentration and the amount of the control variables. The biological system was defined to operate optimally only when the performance function has been minimized during a given time period. By the optimal control theory of Pontoriagin, above biological problem has been converted to a mathematical problem and was solved numerically by multiple shooting method. The calculated trajectory of the optimal control has been asymmetric parabolic one with the maximum at its initiation and the minimum at the middle of total reaction time. This pattern has been consistent with that of probable transient change of the concentration of anesthetic agent when it has been inhalated under the most up to date "Rapid Inhalation Induction" method. The optimal trasient change of the concentration at each compartment has beeb affected by the difference in time dependent nature and the magnitude of the transfer rate. Present theory afforded a method to analyze the control strategy of biological system expressed by compartments model and showed an availability for actual clinical medicine. The optimal control principle must be a most adequate one to describe the Homeostasis in biological system.

We discuss a processor scheduling problem for parallel logic simulation of combinational circuits. In the processor scheduling problem, to be discussed in this paper, for logic simulation using time–first method, the time needed for each gate evaluation is not given beforehand, and is not constant. This feature distinguishes the processor scheduling problem from typical task scheduling problems. First, we devise newly Algorithm MET to solve the processor scheduling problem. The key idea of Algorithm MET is to determine processor scheduling incrementally and dynamically. Then, experimental evaluations using well–known twelve benchmark combinational circuits show the usefulness of Algorithm, MET, compared with conventional static algorithms. We believe that this is a first step to implement parallel logic simulation of combinational circuits.

We propose an optimal throughput problem using graph transformations to maximize throughput of a pipelined data path with some loops. The upper bound of the throughput, equals to the lower bound of the iteration interval between the start of two successive iterations, is limited by the length of a critical loop. Therefore we can maximize the throughput by minimizing the length of the critical loop. The proposed method first schedules an initial Data Flow Graph (DFG) under the initial iteration interval as few as it can use resources, then it transforms the DFG into the flow graph with the minimal length of the critical loop by rescheduling the given initial scheduling result. If there are any control steps which violate the resource constraints owing to the transformations, then these operations are adjusted so as to satisfy given resource consrtraints. Finally by rescheduling the transformed DFG, it gives a schedule with maximum throughput. Experiments show the efficiency of our proposed approach.

A new polarization splitter at optical frequencies is proposed. The basic structure of the device is a tapered velocity coupler which is composed of a straight and a dimensionally tapered slab waveguide on a LiNbO3 substrate. The numerical results obtained with the finite difference method indicate that extinction ratios of polarization less than 2% for both TE and TM modes are possible of realization under moderate control voltages and that the splitting characteristics are stable over a wide range of frequencies.

This paper describes a new method for pose estimation of human face moving abruptly in real world. The virtue of this method is to use a very simple calculation, disparity, among multiple model images, and not to use any facial features such as facial organs. In fact, since the disparity between input image and a model image increases monotonously in accordance with the change of facial pose, view direction, we can estimate pose of face in input image by calculating disparity among various model images of face. To overcome a weakness coming from the change of facial patterns due to facial individuality or expression, the first model image of face is detected by employing a qualitative feature model of frontal face. It contains statistical information about brightness, which are observed from a lot of facial images, and is used in model-based approach. These features are examined in everywhere of input image to calculate faceness" of the region, and a region which indicates the highest faceness" is taken as the initial model image of face. To obtain new model images for another pose of the face, some temporary model images are synthesized through texture mapping technique using a previous model image and a 3-D graphic model of face. When the pose is changed, the most appropriate region for a new model image is searched by calculating disparity using temporary model images. In this serial processes, the obtained model images are used not only as templates for tracking face in following image sequence, but also texture images for synthesizing new temporary model images. The acquired model images are accumulated in memory space and its permissible extent for rotation or scale change is evaluated. In the later of the paper, we show some experimental results about the robustness of the qualitative facial model used to detect frontal face and the pose estimation algorithm tested on a long sequence of real images including moving human face.

The Paper describes a comprehensive system for image recognition based on the technique of boundary spline matching. It can be used to accurately compare two objects and determine whether they are identical or not. The result is extremely satisfactory for comparing planar objects as revealed from the illustrative example presented in this paper. In real practice, images of the same scene object can easily be considered as belonging to different objects if the objects are viewed from different orientations and ranges. Thus, image recognition calls for choosing the proper geometric transformation functions to match images as the initial step so that recognition by template matching can be done as the second step. However, there are a large variety of transformation functions available and the subsequent evaluation of transformation parameters is a highly nonlinear optimisation procedure which is both time consuming and not solution guaranteed, making real-time estimation impossible. This paper describes a new method that represents the boundary of each of two image objects by B-splines and matches the B-splines of two image objects to determine whether they belong to the same scene object. The algorithm developed in this paper concentrates on solving linear simultaneous equations only when handling the geometric transformation functions, which takes almost negligible computational time by using the standard Gaussian Elimination. Representation of the image boundary by B-splines provides a flexible and continuous matching environment so that the level of accuracy can be freely adjusted subject to the requirement of the user. The non-linear optimisation involves only one parameter, i.e. the starting point of each boundary under B-spline simulation, thus guaranteeing a very high speed computational system. The real time operation is deemed possible even there is a wide choice of proper transformation functions.

This paper describes two main technologies for achieving reliable real-time distributed communications systems. One is the technology to prevent the influence of a fault in an autonomous distributed system from spreading to the whole system (called autonomous distributed system control). The other is a software structure based on distributed processing, the object-oriented approach, and layering for better maintainability and expandability (called OO software structure). For the autonomous distributed system control, several inter-subsystem communication methods are proposed and evaluated. From the standpoints of the fault processing and processing load, frames should be sent through a data link over ATM connection and when a fault occurs the link should be switched over without loss of data. A pilot system achieved good reliability without an excessive number of dynamic steps. This autonomous control method will lead to a highly reliable communications system with large capacity. For the OO software structure, this paper gives experimental results from the implementation of a prototype system. Its distributed environment should lead to high reliability by extending the CHILL run-time routine (RTR). This software structure promises to provide service quickly, to reduce costs, and to make the development of each layer's software independent. A real-time OS, e.g., CTRON kernel combined with RTR can give real-time performance, high reliability and high productivity over the distributed system. The use of RTR can reduce the time for the call recovery process.

The access control method adopted by UNIX is simple, understandable, and useful. However, it is quite possible that unexpected information flows occur when we are cooperating with some group members on UNIX. Introducing notions such as "flow right," "maximal permission" and "minimal umask value", this note proposes a simple method, can be seen as a natural extension of UNIX, to control indirect information flows without losing availability and understandability of UNIX.

In this letter we present an electronic circuit based on a neural net to compute the discrete Walsh transform. We show both analytically and by simulation that the circuit is guaranteed to settle into the correct values.

By applying Wigner distribution, which has high time resolution and high random noise reducing capability, to the acoustic bio–signals, the possibility of early diagnosis in both intracranial vascular deformation and prosthetic cardiac valve malfunction increased. Especially in latter case, 1st–order local moment of the distribution showed its effectiveness.

A coupled-mode analysis of a symmetric planar nonlinear directional coupler (NLDC) is presented by using a singular perturbation scheme. The effects of linear coupling and nonlinear modification of refractive index are treated to be small perturbations, and the modal fields of isolated linear waveguides are employed as the basis of propagation model. The self-consistent first-order coupled-mode equations governing the transfer of optical power along the NLDC are obtained in analytically closed form. It is shown that tha critical power for optical switching derived from the coupled-mode equations is in close agreement with that obtained by the numerical analysis using the finite difference beam propagation mathod.

Precise measurements of temperature dependence of the Andreev reflection current for the N–I–S junctions were carried out. Au and Pb were used as N (normal metal) and S (superconducting material), respectively. The experimental results agreed with the analyses based on the Arnold theory.