A systematic theory of the optimum multi-path interpolation using parallel filter banks is presented with respect to a family of n-dimensional signals which are not necessarily band-limited. In the first phase, we present the optimum spacelimited interpolation functions minimizing simultaneously the wide variety of measures of error defined independently in each separate range in the space variable domain, such as 8 8 pixels, for example. Although the quantization of the decimated sample values in each path is contained in this discussion, the resultant interpolation functions possess the optimum property stated above. In the second phase, we will consider the optimum approximation such that no restriction is imposed on the supports of interpolation functions. The Fourier transforms of the interpolation functions can be obtained as the solutions of the finite number of linear equations. For a family of signals not being band-limited, in general, this approximation satisfies beautiful orthogonal relation and minimizes various measures of error simultaneously including many types of measures of error defined in the frequency domain. These results can be extended to the discrete signal processing. In this case, when the rate of the decimation is in the state of critical-sampling or over-sampling and the analysis filters satisfy the condition of paraunitary, the results in the first phase are classified as follows: (1) If the supports of the interpolation functions are narrow and the approximation error necessarily exists, the presented interpolation functions realize the optimum approximation in the first phase. (2) If these supports become wide, in due course, the presented approximation satisfies perfect reconstruction at the given discrete points and realizes the optimum approximation given in the first phase at the intermediate points of the initial discrete points. (3) If the supports become wider, the statements in (2) are still valid but the measure of the approximation error in the first phase at the intermediate points becomes smaller. (4) Finally, those interpolation functions approach to the results in the second phase without destroying the property of perfect reconstruction at the initial discrete points.

This paper describes, based on generation mechanism of conductive noise, that the real conductive noise on AC-mains can't be measured by LISN and 50 Ω-input impedance instrument specified by regulations such as CISPR. Second, it is pointed out that one of the causes of poor reproducibility in radiated emission measurement is the difference among line impedances of AC-mains. Finally, it is insisted that the apparatus such as LISN is necessary for stable measurement of radiated emission, and what improvement on LISN characteristics for higher frequency range should be done is introduced.

A black membrane is a biological-membrane analogue, i.e. a phospholipid bilayer membrane, artificially formed on an orifice immersed in water. It is used to investigate the properties of the membrane itself and channels embedded therein. In this paper, microfabrication techniques are applied to fabricate the orifice, and a glass substrate is isotropically etched to define the orifice geometry. The periphery of the orifice was patterned with aminosilane to anchor the membrane. The remainder part was coated with fluorosilane to make the surface hydrophobic and to prevent adsorption of channel-forming molecules. We demonstrated experimentally that a stable and reproducible membrane is easily obtainable using the orifice.

This paper presents a new microprocessing method that uses a Cl2 fast atom beam (FAB) with stainless steel (SUS304) patterned masks. This new method uses the patterned mask instead of lithographically processed patterned photoresist materials employed in the conventional FAB microprocessing method. We examined the performance of this method by etching GaAs workpieces under various conditions: (1) by setting the distance between the mask surface and flat workpiece surface, L, from 0 µm to 500 µm; (2) by setting the angle between the FAB axis and the flat workpiece surface, θ; to either 30or 50. (3) by etching a workpiece surface that had a 15-µm step and two different surface textures, smooty and undulated; and (4) by doing overlapped etching using a square-patterned mask first and then a circular-patterned mask. The experiments show that the accuracy of reproducing the mask pattern on the etched surface increases with decreasing L. Moreover, the etching rate is almost the same (L100 µm) and decreases slightly at longer distance (L100 µm). The experiments also show that the side walls of the surface are parallel to the FAB axis, even for θ0, indicating that anisotropic etching can be achieved. The experiments for the stepped surface with different surface textures show the surface texture is not affected by the FAB etching. The overlapped etching experiments show that FAB etching is capable of producing overlapped structures. These results demonstrate that this new FAB method can be used in the microproduction of multi-faced, overlapped, three-dimensional microstructures.

It is shown by the derivation of solution methods for an elementary optimization problem that the stochastic relaxation in image analysis, the Potts neural networks for combinatorial optimization and interior point methods for nonlinear programming have common formulation of their dynamics. This unification of these algorithms leads us to possibility for real time solution of these problems with common analog electronic circuits.

In this letter, we demonstrate an experimental CMOS neural circuit towards an understanding of how particular computations can be performed by a T-Model neural network. The architecture and a digital hardware implementation of the learning T-Model network are presented. Our experimental results show that the T-Model allows immense collective network computations and powerful learning.

In this paper, we propose a new class of ID-based non-interactive key sharing scheme with a trusted center which generate a common key on the basis of a linear combination of the center secrets. We also discuss the security of the proposed schemes, and show that the proposed schemes prevent the conventional collusion attack, by adding another random integers unique to each user, on the secret vector that is assigned to the user. Furthermore, we present a new type of a statistical collusion attack which is more suitable for the proposed schemes. We also present the lower bound of the threshold of the statistical collusion attack on the proposed schemes. The proposed schemes can be easily implemented compared with other schemes as they require only computing of the inner product of two vectors over finite ring (including finite field) and an Euclidean quotient, for generating the common key. Our proposed schemes can be regarded as modified versions of the Blom's original scheme. However our proposed schemes are secure against our new type of the attack, as well as the collusion attack based on the solving of the linear equations, although Blom's scheme is insecure against both of these collusion attacks.

Telecommunications management activities have mostly been supported by operators; however, machines are gradually playing more important roles in the management arena by utilizing computing technology. Additionally, management systems can now be networked by using standard interface specifications. The study of human and machine integration is thus essential for achieving the sophisticated management objectives of telecommunications. This paper proposes the principles for a telecommunications management integration network (TMIN), which integrates human and machine management networks, and proposes a source text description method for transferring management communication knowledge from human to machine. First, reference models are proposed for the management process and management communication. These models cover network management activities of both humans and machines. Second, the contents of the source text are clarified. Source text presents human management knowledge in a form suitable for machine-machine communication. Third, an efficient source text description method is proposed that reduces redundancy and proliferation. Finally, a means of harmonizing management information definitions with TMIN is suggested to facilitate human-machine cooperation.

Memory type polymer dispersed liquid crystal (PDLC) can be applied to a thermal addressing display device cell. Making use of its easy fabrication of large area display using flexible film substrate, the PDLC film can be used as reusable paper for direct-view mode display. In this study, memory type PDLC cells are prepared with an aluminum reflector deposited onto one side of the substrate and the reflection property in the PDLC cell with the reflector is clarified and compared to that without the reflector in the off-, on- and memory-states. The increase of contrast ratio and the decrease of driving voltage can be concurrently realized by decreasing the cell thickness by attaching the reflector. In addition, the reflected light in the off-state is bright and colorless due to the reflector, as compared with the weak, bluish reflected light in the cell without the reflector. Reflected light in the on-state and the memory-state are tinged with blue.

Self-modelocking of Ti:sapphire laser has obtained with less than 2 W of argon-ion laser pumping. Two independent lasers with 36 fsec and 63 fsec in pulse duration were operated by a 6 W pump laser. In the low-threshold lasers, not only an ordinary mode-locking but also a double-pulse mode-locking, where two pulses circulating in the cavity, was stable.

Managed Objects (MOs) can be specified by the combination of a static information model and a dynamic process model. First, this paper presents a mapping of attributes from a process model diagram to an information model diagram. Then, it introduces a concept of topology into these two models and proposes a hypothesis about the relationship of topology in these two models. To explicitly explain the hypothesis, it can be stated that all attributes of incoming or outgoing data related to a process in a process model are mapped to an information model where these attributes are interconnected by an explicit relationship which corresponds to a specific meaning, such as physical containment or logical connection. From an intuitive perspective, it can be said that if two attributes have a close topological relationship in a process model, the mapped attributes also have a close topological relationship in an information model. This hypothesis provides clues for determining whether there is an error in an attribute either in the process model or in the information model. By examining the way attributes of incoming or outgoing data related to a process are mapped to an information model, we can detect whether there is an error with respect to the process. The error correction is performed with the assistance of probability analysis. The method of error detection and correction can be implemented in a computer aided tool. Then, error detection on the attribute level becomes automatic, and error correction on the attribute level becomes interactive through the computer aided tool. Finally, the validity of the hypothesis is confirmed by analyzing ITU-T Recommendation M.3100. The specification of the fabric object class defined in M.3 100 is transformed into these two models and the hypothesis is validated for the analysis of the mapping between these two models.

This paper proposes a multi-fisheye distortion method which can show a large-scale telecommunication network in a single window on the display of a workstation or personal computer. This distortion method has three advantages over the conventional single-fisheye distortion method. First, the focus area is magnified smoothly by the fisheye distortion method, and the peripheral area coordinates are calculated linearly to avoid unnecessary distortion. Second, multiple focus areas are magnified smoothly by using an average of the coordinates calculated for the individual focuses. Third, the scale of unnecessary areas is reduced to provide sufficient space for magnification. The effectiveness of this method is demonstrated by applying to the display of large-scale networks. The effect of the resulting network map distortion on the user is tested by a subjective evaluation experiment.

Most current management systems employ graphic-user-interface displays to visualize the networks being managed. Some networks are so large that it is difficult to display all network elements in a single window alone, and therefore, the hierarchical multi-window style presentation is commonly used. This form of presentation has disadvantages, however, including the fact that window manipulations are complex. Our approach (bifocal network visualization) is able to display both the context and any detail of a network within a single window, and overcomes the disadvantages of hierarchical multi-window presentation. We implemented this bifocal network visualization on a workstation using a frame buffer memory called DUALQUEST that is able to generate images in real-time and is simple to operate. This paper describes bifocal network visualization and its implementation. Furthermore, we present an experiment to compare our interface with conventional hierarchical multi-window presentation.

This paper proposes a new approach to the management of large-scale communication networks. To manage large-scale communication networks effectively, it is essential to get a bird's-eye view of them when they are in their normal conditions. When an indication of faulty state is detected, the focus of the management is narrowed down to the faulty network elements until the appropriate granularity is reached. This management scheme is called multilevel network management in this paper, and it first explains the significance of this scheme for large-scale communication networks and presents some ideas on implementing this management scheme. It then proposes that system identification be used in multilevel network management. The system identification is used to measure transmission delays between two arbitrarily selected nodes in the networks, and multilevel network management is achieved by selecting those two nodes appropriately in accordance with the levels to be managed. Finally, it is demonstrated by computation simulation results that the proposed method is suitable for multilevel network management.

Trouble management is a key function in solving the problems and maintaining the high communications capability of a network when communication service network users encounter problems in the quality of services [1]. This paper proposes technologies and architecture for an intelligent management system to achieve advanced service/network trouble management. The system generates operation scenarios to find a cause to solve a reported trouble, executes them, and modifies them according to operation circumstance changes. In the scenario execution process, fault propagation simulation is used to isolate a fault in necessary cases. The evaluation of the system applied to the ISDN services shows that the proposed system can achieve high-speed, precise trouble management by the integrated cooperative work of a human (operator) and a machine (operation system).

This paper proposes a suitable distributed computing model as the basis for building a network management system. Author has been studying a distributed reactive model, called Meta for this purpose at Cornell University. Effectiveness using Meta is to provide high level program interface for developing network management system, and programmers can achieve network management system with coding small amount of programs. It also realizes easy additions and modifications for network management application programs. To confirm the effectiveness of the proposal, the author has utilized Meta to implement an experimental network management system. The experimental system provides high level interfaces for monitoring and controlling network components. It also supports reliable communication over distributed nodes. Preliminary evaluation of the system shows that critical network management applications are provided within an appropriate response time for all applications provided by SNMP, with small development cost and easy system modification.

The availability of new technologies in the computer and network industry has allowed us to benefit from a wider choice when building new information systems. This paper presents Japan Airlines' challenge to develop a new information network and management infrastructure based on the new technology. Compared with the existing main-frame environment, the new infrastructure will give us a more comfortable and economic network computing environment. Once we think about network management, there are so many issues to be solved. All existing network elements have their own management consoles with different interfaces and commands. Net managers are swimming in the pool of system consoles looking for the one that exactly tells them what is going on at the user site. The industry standard SNMP offers us a much better environment. However, there is still a long way to go before reaching a world where net managers find a single management console with a single object to manage that is composed of all network elements.

In this paper a method of recognizing waveform based on the Discrete Wavelet Transform (DWT) presented by us is applied to detecting the K-complex in human's EEG which is a slow wave overridden by fast rhythms (called as spindle). The features of K-complex are extracted in terms of three parameters: the local maxima of the wavelet transform modulus, average slope and the number of DWT coefficients in a wave. The 4th order B-spline wavelet is selected as the wavelet basis. Two channels at different resolutions are used to detect slow wave and sleep spindle contained in the K-complex. According to the principle of the minimum distance classification the classifiers are designed in order to decide the thresholds of recognition criteria. The EEG signal containing K-complexes elicited by sound stimuli is used as pattern to train the classifiers. Compared with traditional method of waveform recognition in time domain, this method has the advantage of automatically classifying duration ranks of various waves with different frequencies. Hence, it specially is suitable to recognition of signals which are the superimposition of waves with different frequencies. The experimental results of detection of K-complexes indicate that the method is effective.

In this paper, we consider ZKIPs for promise problems. A promise problem is a pair of predicates (Q,R). A Turning machine T solves the promise problem (Q,R) if, for every x satisfying Q(x), machine T halts and it answers "yes" iff R(x). When ¬Q (x), we do not care what T does. First, we define "promised BPP" which is a promise problem version of BPP. Then, we prove that a promise problem (Q,R) has a 3-move interactive proof system which is black-box simulation zero knowledge if and only if (Q,R) ∈ promised BPP. Next, we show a "4-move" perfect ZKIPs (black-box simulation) for a promise problem of Quadratic Residuosity and that of Blum Numbers under no cryptographic assumption.

Wavelength-division multiplexing (WDM) optical switching networks are one of most attractive technologies in optical interconnections. By combining with time-division multiplexing (TDM) and space-division multiplexing (SDM) technologies, remarkably high-throughput interconnections may be accomplished. In this paper, we propose WDM switching networks with time-division multiplexed optical signals by using free-space optics. We also propose novel WDM interconnections, including multiple-wavelength light-sources, optical fibers and wavelength-selectable detectors. We successfully confirmed basic principles for the WDM interconnections.