In this paper we suggest the "goodness" of models using the imformation criterion AIC. The information criterion AIC is a statistic to estimate the badness of models. When we usually make the fuzzy rules, we aim to minimize inference error and the number of rules. But these conditions are the criteria to acquire an optimum rule-model by using the training data. In the general case of fuzzy reasoning, we aim to minimize the inference error for not only given training data, but also unknown data. So we have introduced a new information criterion based on AIC into the appraised criterion for estimating the acquired fuzzy rules. Experimental results are given to show the validity of using AIC.

High-speed display of 3-D objects in virtual reality environments is one of the currently important subjects. Shape simplification is considered an efficient method. This paper presents a method of hierarchical cube-based segmentation for shape simplification and multiresolution model construction. The relations among shape simplification, resolution and visual distance are derived firstly. The first level model is generated from scattered range data by cube-base segmentation with the first level cube size. Multiresolution models are then generated by re-sampling polygonal patch vertices of each former level model with hierarchical cube-based segmentation structure. The results show that the algorithm is efficient for constructing multiresolution models of free-form shape 3-D objects from scattered range data and high compression ratio can be obtained with little noticeable difference during the visualization.

We have developed a management agent that adapts the delegation concept to achieve efficient network management. In conventional delegation architecture, a network management operator details management operations in an operation-script that describes management operation flow and such network management functions as event management and path tracing. The operator sends this script to agents to execute. In our delegation architecture, the operator sends only a script skeleton describing management operation flow alone; management functions are built into the agents in the form of fuction objects. This helps keep management traffic low. Each function object is designed by utilizing three operational objects: enhanced, primitive, and communication. Each enhanced operational object (EOO) provides a script skeleton with an individual network management function. A primitive operational object (POO) provides an EOO with managed object (MO) access functions. A communication operational object (COO) provides an EOO with a mechanism for accessing the functions of other remote EOOs. We have tested our design by applying it to a path tracing application, and we have measured the total data transfer size between a manager and an agent and the amount of memory usage in our agent's running environment. Evaluation of our implementation suggests that our design can be applied such network management functions as connection establishment and release, fault isolation, and service provisioning.

An advanced intelligent network (IN) provides service management along with telecommunication services, and has a two-layer architecture, i.e., a transmission layer and an intelligent layer. An advanced IN's programmability is achieved by a service-independent platform of nodes in the intelligent layer, and service-dependent software called logic programs. In contrast to telecommunication services, models for service management have not yet been established. This paper presents both execution and specification models for service management. The execution model is composed of three hierarchies that apply to various kinds of management operation. The specification model has the capability to define the details of data items. The specification language for service management is also proposed. Simulation on dynamic SQL based DBMS solved that; (1) Logic programs for service management can be made small size on the model, and (2) To provide efficient database operation, programmability must be enhanced if service management includes table with variable number of field operation.

This paper proposes a new AFC (automatic frequency control) circuit employing a double-product type frequency discriminator to enable fast acquisition in very-low CNR (carrier to noise power ratio) environments. The frequency step responses of the proposed AFC circuit are theoretically analyzed. In addition this paper evaluates the performance of the proposed AFC circuit by computer simulation in very-low CNR environments. The simulation results confirm that click noise at the frequency discriminator causes large frequency tracking error and that this error can be improved by increasing the delay time of the double-product type frequency discriminator. The frequency error can be also reduced by introducing the proposed frequency discriminator to modify the frequency error detection performance. The acquisition time of the proposed AFC circuit can be reduced by about 100 symbols compared to the conventional cross-product type AFC circuit.

This paper describes new problems in delay analysis for high-performance LSI design and presents a static delay analysis tool PCHECK. PCHECK is characterized by (1) a new critical path trace algorithm for avoiding the error caused by signal transient time and (2) a precise delay calculation model for resistive shielding. Experimental results show that the delay calculation error in the worst case is less than 20 ps.

This paper analyzed the connection points of Main Distribution Frames (MDF), which are installed between outside plants and inside plants (service nodes). This paper also proposes a connecting system for forthcoming FITL (Fiber In The Loop) networks. NTT has developed the Subscriber Line Cross-Connecting Module (LXM) for the FITL network and will continue to introduce LXMs and deploy optic subscriber networks in big cities throughout Japan.

This paper describes how to effectively use discriminative training based on Minimum Classification Error (MCE) criterion for a small amount of data in order to attain the highest level of recognition performance. This method is a combination of MCE training and Vector-Field-Smoothed Bayesian learning called MAP/VFS, which combines maximum a posteriori (MAP) estimation with Vector Field Smoothing (VFS). In the proposed method, MAP/VFS can significantly enhance MCE training in the robustness of acoustic modeling. In model training, MCE training is performed using the MAP/VFS-trained model as an initial model. The same data are used in both trainings. For speaker adaptation using several dozen training words, the proposed method has been experimentally proven to be very effective. For 50-word training data, recognition errors are drastically reduced by 47% compared with 16.5% when using only MCE. This high rate, in which 39% is due to MAP, an additional 4% is due to VFS, and a further improvement of 4% is due to MCE, can be attained by enhancing MCE training capability by MAP/VFS.

We present a topological framework of stepwise specification for concurrent systems in this paper. Some of description techniques can make topologies on the system space. Such topologies corresponds to abstract levels of those description techniques. Using a family of such description techniques, one can specify systems stepwisely. This framework allows to bridge various DTs and modularizing, so that global properties and module properties of systems become to be related to each other. Within this framework, we show derivation of a LOTOS cpecification from temporal logic formulae. An extended version of LOTOS with respect to concurrency is used in this paper. A semantics including concurrency is introduced to do this in this method. The method presented in this paper is applied to mobile telecommunication.

The printed dipole on a semi-infinite substrate is investigated. The solution is based on the moment method in the Fourier transform domain. We analyze far-field and near-field radiation patterns for a printed dipole. Therefore, we make radiation fields clear.

In this paper, a new explicit transformation method between Bezier and polynomial representation is proposed. An expression is given to approximate (n + 1) Bezier control points by another of (m + 1), and to perform simple and sufficiently good approximation without any additional transformation, such as Chebyshev polynomial. A criterion of reduction is then deduced in order to know if the given number of control points of a Bezier curve is reducible without error on the curve or not. Also an error estimation is given only in terms of control points. This method, unlike previous works, is more transparent because it is given in form of explicit expressions. Finally, we discuss some applications of this method to curve-fitting, order decreasing and increasing number of control points.

An individual identification system is developed. In this system, we unify profile curve identification and full face image identification to obtain more successful recognition rate. In profile cruve identification process, the P-type Fourier descriptor is made use of. In full face image identification process, mosaic density values are made use of. A combination of the two processes shows higher recognition rates than those obtained by each single process.

In the usual optical flow detection, the gradient constraint, which expresses the relationship between the gradient of the image intensity and its motion, is combined with the least-squares criterion. This criterion means assuming that only the time derivative of the image intensity contains noise. In this paper, we assume that all image derivatives contain noise and derive a new optical flow detection technique. Since this method requires the knowledge about the covariance matrix of the noise, we also discuss a method for its estimation. Our experiments show that the proposed method can compute optical flow more accurately than the conventional method.

The uncertainty involved in the gradient constraint for optical flow detection is often modeled as constant Gaussian noise added to the time-derivative of the image intensity. In this paper, we examine this modeling closely and investigate the error behavior by experiments. Our result indicates that the error depends on both the spatial derivatives and the image motion. We propose alternative uncertainty models based on our experiments. It is shown that the optical flow computation algorithms based on them can detect more accurate optical flow than the conventional least-squares method.

The effects of α-particle-induced parasitic bipolar current on soft errors in submicron 6-transistor SOI SRAMs were numericaly studied. It was shown that the bipolar current induces soft errors and that there exists a critical quantity which determines the soft error occurrence in the SOI SRAMs. Simulated soft error rates were in the same order as those for bulk SRAMs.

A algorithm for designing a pattern classifier, which uses MDL criterion and a binary data structure, is proposed. The algorithm gives a partitioning of the range of the multi-dimensional attribute and gives an estimated probability model for this partitioning. The volume of bins in this partitioning is upper bounded by ο((log N/N)K/(K+2)) almost surely, where N is the length of training sequence and K is the dimension of the attribute. The convergence rates of the code length and the divergence of the estimated model are asymptotically upper bounded by ο((log N/N)2/(K+2)). The classification error is asymptotically upper bounded by ο((log N/N)1/(K+2)). Simulation results for 1-dimensional and 2-dimensional attribute cases show that the algorithm is practically efficient.

In order to produce high quality multimedia contents efficiently, DTPP -desktop program production system- has been proposed. The DTPP is capable of supporting all the necessary procedures of program production, from planning to broadcasting, by molding each process into the desktop environment of program producers. The DTPP system consists of multimedia terminals, a media server, a computing server, and network system. In the DTPP, new technological concepts such as cooperative program production, indexing and utilization of attribute information of images, and video components and spatio-temporal editing will be installed.

Time-critical-communication, which should guarantee a time limit of a communication service is getting important in multimedia and factory automation fields. This paper proposes an IP-based protocol, Network Protocol with Performance (NPP) to provide the advanced best-effort service which takes a time constraint into account for real-time applications on the Internet. NPP uses the packet-scheduling function to make an effort to guarantee time constraints. Packet-scheduling algorithm chooses a packet in a NPP queue by a precedent level and a time constraint of each packet. We also discuss an application of NPP to multimedia communication system, and investigate performance of NPP by simulation.

Through comparing the results of two successive IPTP Character Recognition Competitions which focused on 3-digit handprinted postal codes, we herein analyze the methodologies of the submitted algorithms along with the substituted or rejected patterns of these algorithms. Regarding their methodologies, lesser diversity was apparent specifically concerning the contour-chain code based on local stroke directions and statistical discriminant functions for feature extraction and discrimination. Analysis of the patterns demonstrated that the misrecognized patterns being most often improved were categorized as a decrease in peculiarly shaped handwritten characters or heavy-handed and disconnected strokes. However, most of the remaining misrecognitions were still classed as peculiarly shaped handwriting as commonly shared between the best three algorithms. From these analyses, we could delineate a direction to be taken for developing more effective methodologies and clarify the remaining problems to be overcome by the subsequent intensive research. Furthermore, we evaluate in this article our multi-expert recognition system for achieving higher recognition performances by means of combining complementary recognition algorithms. We performed a subsequent investigation of the Candidate Appearance Likelihood Method using novel experimental conditions and a new examination of the application of the neural network as the combining method for accumulating the broader candidate appearances. The results obtained confirm that combining through the neural network constitutes one of the most effective ways of making the multi-expert recognition system a reality.

We propose a new algorithm for minimizing the number of vertices of an approximate curve by keeping the error within a given bound (min-# problem) with the parallel-strip error criterion. The best existing algorithm which solves this problem has O (n2 log n) time complexity. Our algorithm which uses the Cone Intersection Method does not have an improved time complexity, but does have a high efficiency. In particular, for practical data such as those which represent the boundaries or the skeletons of an object, the new algorithm can solve the min-# problem in nearly O(n2) time.