This paper describes that a neural network, which consists of neurons with piecewise–linear sigmoid characteristics, is able to approximate any piecewise–linear map with origin symmetry. The neural network can generate "deterministic diffusion" originating from its diffusive trajectory.

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 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.

Introducing a general statistical model of image noise, we present an optimal algorithm for computing 3-D motion from two views without involving numerical search: () the essential matrix is computed by a scheme called renormalization; () the decomposability condition is optimally imposed on it so that it exactly decomposes into motion parameters; () image feature points are optimally corrected so that they define their 3-D depths. Our scheme not only produces a statistically optimal solution but also evaluates the reliability of the computed motion parameters and reconstructed points in quantitative terms.

Based on a newly proposed notion of relational network, a novel learning mechanism for model acquisition is developed. This new mechanism explicitly deals with both qualitative and quantitative relations between parts of an object. Qualitative relations are mirrored in the topology of the network. Quantitative relations appear in the form of generalized predicates, that is, predicates that are graded in their validity over a certain range. Starting from a decomposition of binary objects into meaningful parts, first a description of the decomposition in terms of relational networks is obtained. Based on the description of two or more instances of the same concept, generalizations are obtained by first finding matchings between instances. Generalizing itself proceeds on two levels: the topological and the predicate level. Topological generalization is achieved by a simple rule-based graph generalizer. Generalization of the predicates uses some ideas from MYCIN. After successful generalization, the system attempts to derive a simple and coarse description of the achieved result in terms of near natural language. Several examples underline the validity of relational networks and illustrate the performance of the proposed system.

A method is presented for reconstructing the surface profile of a perfectly conducting rough surface boundary from the measurements of the scattered far-field. The proposed inversion algorithm is based on the use of the Kirchhoff approximation and in order to determine the surface profile, the Fletcher-Powell optimization procedure is applied. A number of numerical results illustrating the method are presented.

Multimedia services based on broadband ISDN (B-ISDN) technology need a network architecture that satisfies the requirements of users, carriers, and vendors. This paper describes a new network architecture for B-ISDN service control and management based on INA. We list general requirements, and present implementation issues of INA. A network architecture and main components, which resolve implementation issues, is then proposed. We also describe a video-on-demand service based on our proposed architecture.

An active contour model which is called Snakes was proposed to extract the border line of an object from an image. This method presents the minimization problem of the energy function defined on the contour curve. The authors obtained an excellent result by applying genetic algorithm to the contour extraction. In this paper, the biphased genetic algorithm, which is a new type of genetic algorithm, is proposed to minimize the energy function of Snakes. The parameters of the genetic algorithm are examined to tune up its local and global search abilities. The biphased genetic algorithm composed of two phases of genetic search is constructed to use both abilities of the exploration and the exploitation properties of the genetic algorithm. The processing results of the biphased genetic algorithm are compared with those of the previous methods, and the advantages of the proposed algorithm are shown by several experiments.

A new approach using radiation mode expansions is presented for calculating radiated fields from arbitrary distribution of electromagnetic sources in the half space region partitioned by a dielectric layer with a ground conductor. This method is applied to the calculation of radiation from microstrip-type antennas with a dielectric substrate of theoretically infinite extent. To be able to use this method, it is necessary to obtain first the field distribution around antenna patches, which is accomplished rather easily by using the FD-TD method. Radiation pattern calculations are presented for a rectangular patch antenna to verify the feasibility of this approach.

This letter proposes the method using a filter to suppress the very large noise obstructive to the radio pulsar surveys. This noise suppression filter is constructed from the average of the amplitude spectrum of pulsar signal for each channel. Using this method, the dispersion measure, one of the important parameters in the pulsar surveys, can easily be extracted.

We have classified parenchymal echo patterns of cirrhotic liver into 3 types, according to the size of hypoechoic nodular lesions. We have been studying an ultrasonic image diagnosis system using the three–layer back–propagation neural network. In this paper, we will describe the applications of the neural network techniques for recognizing and classifying chronic liver disease, which use the nodular lesions in the Proton density and T2–weighed magnetic resonance images on the gray level of the pixels in the region of interest.

A simple numerical method for calculating paths of creeping rays around an arbitrary convex object is presented. The adventage of this method is that the path of creeping ray is iteratively determined from initial values of incident point and incident direction of the creeping ray without solving differential equation of geodesic path. As the numerical examples, the path of creeping ray on the prolate spheroid and the resonance path of natural modes are shown.

Along with the improvement of micro processors and local area networks, a distributed system becomes useful to realize a telecommunication system. It has potential advantage to achieve both high performance and high reliability. However, the design of a distributed system tends to be more complicated compared to a conventional centralized system. For the purpose of the standardization of distributed processing, ISO and ITU-T study the Open Distributed Processing (ODP) and are currently standardizing the Basic Reference Model of ODP (RM-ODP). To avoid dealing with the complexity of distributed systems, RM-ODP defines five viewpoints. The viewpoint approach of RM-ODP is proposed as a framework for the design of a distributed system. Although some previous works give the design methods of distributed systems based on the ODP viewpoint approach, the detailed design method has not been fully specified or all of the five viewpoints are not taken into account. In this paper, we describe a detailed design method for a distributed telecommunication system based on the ODP viewpoint approach. The method applies the five viewpoints to the three phases of design of a distributed system, that is, requirement analysis, functional design and detailed design phase. It clarifies what specifications for the target system should be made from the individual viewpoints and how the specifications are related each other. It also takes account of the platform which provides the distribution support, and gives the design method for both the platform and the application specific functions on the platform. The design method is examined by applying it to the design of a distributed MHS system supporting X.400 series protocols. In this example, the remote procedure call based on the client-server model is selected as the base of the platform. The result shows that our method is useful to simplify the complexity of the design for a distributed telecommunication system.

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.

The propagation characteristics of dielectric waveguides with slanted grating structure are analyzed by using the combination of the improved Fourier series expansion method and the approximated multilayer method. The slanted grating region is appoximated by a structure with stratified thin modulated index layers. This method is effective to the guiding problems of the planar slanted grating, because the electromagnetic fields in each layer can be expressed by shifting the phase of the solution in the first layer. In this paper, numerical results are given for the grating with the rectangular and the sinusoidal profile for arbitrary slant angle. The radiation efficiencies for the grating with negative and positive slant angle are also discussed.

With advances in the speed, bandwidth and reliability of telecommunications networks and in the performance of workstations, distributed processing has become widespread. Information sharing among distributed nodes and its mutual exclusion are of great importance for efficient distributed processing. This paper systematizes and quantitizes a shared memory called Data-Cyclic Shared Memory (DCSM) from the viewpoints of memory organization and access mode. In DCSM, the propagation delay of transmission lines and the data relaying delay in each node are used for information storage, and memory information encapsuled in the form of "memory cells" circulates infinitely in a logical ring type network. The distinctive feature of DCSM, in addition to the way data is stored, is that data and the access control are completely distributed, which contrasts with existing memory where both are centralized. Therefore, there are no performance bottlenecks caused by concentrating memory access. Distributed Shared Memory (DSM), which has a scheme similar to DCSM's, has also been proposed for distributed environments. In DSM, the data is also distributed but the control for accessing each data is centralized. From the viewpoints of memory organization and the access method, DCSM is very flexible. For instance, word length can be spatially varied by defining data size at each address, and each node can be equipped with mechanisms for special functions such as the content address specification and asynchronous report of change in contents. Because of this flexibility, it can be called a "software-defined memory." The analysis also reveals that DCSM has the disadvantages of large access delay and small memory capacity. The capacity can be enlarged by inserting FIFO type queues into the circulation network, and the delay can be shortened by circulating replicas of original memory cells. However, there is a trade off between the maximal capacity and the mean access time. DCSM has many potential applications, such as in the mutual exclusion control of distributed resources.

It is shown that a self–recurrent fuzzy inference can cause chaotic responses at least three membership functions, if the inference rules are set to represent nonlinear relations such as pie–kneading transformation. This system has single input and single output both with crisp values, in which membership functions is taken to be triangular. Extensions to infinite memberships are proposed, so as to reproduce the continuum case of one–dimensional logistic map f(x)=Ax(1–x). And bifurcation diagrams are calculated for number N of memberships of 3, 5, 9 and 17. It is found from bifurcation diagrams that different periodic states coexist at the same bifurcation parameter for N9. This indicates multistability necessarily accompanied with hysteresis effects. Therefore, it is concluded that the final states are not uniquely determined by fuzzy inferences with sufficiently large number of memberships.

In this paper we study the bifurcation phenomena of quasi–periodic states of a model of the human circadian rhythm, which is described by a system of coupled van der Pol equations with a periodic external forcing term. In the system a periodic or quasi–periodic solution corresponds to a synchronized or desynchronized state of the circadian rhythm, respectively. By using a stroboscopic mapping, called a Poincar mapping, the periodic or quasi–periodic solution is reduced to a fixed point or an invariant closed curve (ab. ICC). Hence we can discuss the bifurcations for the periodic and quasi–periodic solutions by considering that of the fixed point and ICC of the mapping. At first, the geometrical behavior of the 3 generic bifurcations, i.e., tangent, Hopf and period doublig bifurcations, of the periodic solutions is given, Then, we use a qualitative approach to bring out the similar behavior for the bifurcations of the periodic and quasi–periodic solutions in the phase space and in the Poincarsection respectively. At last, we show bifurcation diagrams concerning both periodic and quasi–periodic solutions, in different parameter planes. For the ICC, we concentrate our attention on the period doubling cascade route to chaos, the folding of the parameter plane, the windows in the chaos and the occurrence of the type I intermittency.

In general, message passing multiprocessors suffer from communication overhead and shared memory multiprocessors suffer from memory contention. Also, data I/O overhead limits performance. In particular, computer vision tasks that require massive computation are strongly affected by these disadvantages. This paper proposes new parallel architectures for computer vision, a Flexibly (Tightly/Loosely) Coupled Multiprocessor (FCM) and a Flexibly Coupled Hypercube Multiprocessor (FCHM) to alleviate these problems. FCM and FCHM have a variable address space memory in which a set of neighboring memory modules can be merged into a shared memory by a dynamically partitionable topology. FCM and FCHM are based on two different topologies: reconfigurable bus and hypercube. The proposed architectures are quantitatively analyzed using computational models and parallel vision algorithms are simulated on FCM and FCHM using the Intel's Personal SuperComputer (iPSC), a hypercube multiprocessor, showing significant performance improvements over that of iPSC.

This paper describes a procedural detailed compaction method for the symbolic layout design of CMOS leaf cells and its algorithmic aspects. Simple symbolic representations that are loosely designed by users in advance are automatically converted into densely compacted physical patterns in two phases: symbolic–to–pattern conversion and segment–based detailed compaction. Both phases are executed using user-defined procedures and a specified set of design rules. The detailed compaction utilizes a segment–based constraint graph generated by an extended plane sweep method where various kinds of design rules can be applied. Since various kinds of basic operations can be applied to the individual segments of patterns in the procedures, the detailed procedure for processing can be described in accordance with fabrication process technologies and the corresponding sets of design rules. This combined stepwise procedure provides a highly flexible framework for the symbolic layout of CMOS leaf cells. The proposed approach was implemented in a symbolic layout system called CAMEL. To date, more than 300 kinds of symbolic representations of CMOS leaf cells have been designed and are stored in the database. Using several different sets of design rules, symbolic representations have been automatically converted into compacted patterns without design rule violations. The areas of those generated patterns were averaged at 98% of the manually designed patterns. Even in the worst case, the increases in area were less than about 10% of the manually designed ones. Furthermore, since processing times are much shorter than manual design periods, for example, 300 kinds of symbolic representations can be converted to corresponding physical patterns in only a day. It is evident, through these practical design experiences with CAMEL, that our approach is more flexible and process–tolerant than conventional ones.