The performance of a nonblocking switch with two kinds of correlated input calls is analyzed. We define two kinds of calls as the waiting call and the immediate call, and assume that the immediate call has the priority over the waiting call. If the traffic density of one kind of calls is larger than maximum throughput, the ratio of the corresponding kind of calls to the total traffic must be restrained in some range. We derive the maximum ratio of the waiting call by using two approximate methods. The effects of traffic densities and transition probabilities of two kinds of calls on the maximum ratio of the waiting call are also considered. It is shown that, if the traffic density of the immediate call is smaller than that of the waiting call, our approximate methods are useful to derive the maximum ratio of the waiting call to the total traffic.

The discrete-time short-time Fourier transform (STFT) is known as a useful tool for analyzing and synthesizing signals. This paper introduces an extention of the well-known STFT to a general form which is more suitable for high resolutional signal analysis. A channel frequency division scheme is developed for realizing arbitrary bandwidth and center frequency so as to improve resolution performance. It is based on a nonuniform filter bank structure with integer decimation and interpolation factors. A design example of the generalized STFT using symmetric windows is given.

Recently as one of attractive applications in the B-ISDN era, LAN/MAN interconnection through an ATM network has been coming up because burstiness of LAN/MAN data traffic is applicable to distinctive features of cell based ATM network. In order to overcome a difference of the connection mode, i.e., CL packet transfer of LAN/MAN and CO cell transfer of ATM network, a number of interworking and bandwidth allocation mechanisms have been proposed. These methods, however, indicate both merits and drawbacks concerning with CL data transfer quality, network resource efficiency and processing overhead in IWU/CLS and the network, and have been mostly evaluated only for a single IWU model. This paper aims at showing the most appropriate method of LAN/MAN interworking for IWU-IWU or IWU-CLSF connection. In the paper, some interworking issues including a general qualitative assessment are clarified. We then evaluate the selected five interworking methods based on Bandwidth Renegotiation (BR) and VC Establishment (VCE), which are combined with Traffic Enforcement Functions (TEFs) based on policing mechanisms and Cell Loss Control (CLC) scheme. By transient and stationary simulation approach for a single IWU and an IWU-CLS connection model, the most applicable method is indicated as a case study from view points of the communication quality, effective use of the bandwidth and processing load.

Circuit access control is a traffic control technique of rejecting calls arriving at a group of specified circuits to make the group free at a target scheduled time so that the capacity may be dynamically reallocated to serve other traffic demand. This technique plays an important role for resource allocation control in state-of-the-art capacity reconfigurable networks as well as for switching calls on a reserved basis in the ISDNs. In this paper, we present a novel adaptive scheme for circuit access control in order to overcome the inefficiency of the conventional deterministic scheme. The presented scheme is based only on knowledge about service time and bandwidth characteristics of calls. The transitional behavior of the circuit group under the scheme is analyzed, and the gain in utilization achieved by the adaptive scheme is examined. We treat a model of the circuit group shared by multi-slot calls with different service times, and describe the results of the transient analysis and the approximation method for evaluating the gains.

Connectivity (of node-to-node) is generally used to examine the robustness of graphs. When telecommunication network switches are integrated into logical switching areas, we should examine node-to-area connectivity rather than node-to-node connectivity. In a previous paper, we proposed node-to-area (NA) connectivity using area (subset of nodes) graph. In this paper, we consider a further constraint: "there is a path that does not include other nodes in the source node area." We call this property, directly NA-connected. Application of this constraint makes telecommunications networks robust against locally striking disasters. The problem of finding the maximum number of edge deletions that still preserves the direct NA-connection is shown to be NP-hard. It was shown in our previous paper that an NA-connected spanning tree is easily found; this paper shows that the problem of finding a directly NA-connected spanning tree is also NP-hard. We propose an O(|E||X|) approximation algorithm that finds a directly NA-connected spanning subgraph with an edge nummber not exceeding 2|V|3 for any NA-connected area graph that satisfies a described simple condition. (|V|,|E|,and |X| are the numbers of nodes, edges, and areas, respectively.)

Degradation of metal-oxide-semiconductor field-effect transistors (MOSFETs) reliability such as the relative transconductance reduction by plasma exposure is evaluated. The linear region peak transconductance (gm) decreases with antenna ratio (exposed antenna area/gate area) due to the plasma-induced Si-SiO2 interface state generation. The Si-SiO2 interface-related gm reduction which is defined as (gm0gm)/gm, where gm0 is the initial value of gm, decreases as the gate oxide thickness decreases. It is also found that the decreasing amount of gm depends on the conduction current from the plasma. The correlation between the (gm0gm)/gm and the plasma-induced reduction of charge-to-breakdown of the gate oxide with a constant current stress (ΔQBD) is observed, and the result shows that the gm reduction of nMOSFET during the plasma process is severe to the plasma-induced damage compared with the gate oxide breakdown.

The Double-Sided Rugged poly Si (DSR) technology has been developed for high density DRAMs. The DSR technology was achieved using transformation of rugged poly Si caused by ion implantation. The DSR can increase the surface area of the storage electrode, because it has rugged surfaces on both upper and lower sides. The 2-FINs STC (STacked Capacitor cell) with DSR was fabricated in the cell size of 0.72 µm2, and it is confirmed that the DSR can increase the surface area 1.8 times larger than that of smooth poly Si. It is expected that 25 fF/bit is obtained with a 300 nm-thick storage electrode. These effects show that sufficient capacitance for 256 Mb DRAMs is obtained with a low storage electrode. It is confirmed that there is no degradation in C-V and I-V characteristics. Moreover, the DSR needs neither complicated process steps nor special technologies. Therefore, the DSR technology is one of the most suitable methods for 256 Mb DRAMs and beyond.

The performance of the hybrid-ARQ scheme with a convolutional code, in which the retransmission criterion is based on an estimated decoding error rate, is evaluated for moderately time-varying channels. It is shown by computer simulations that the simple average diversity combining scheme can almost attain the same performance as the optimally weighted diversity combining scheme. For the whole and partial retransmission schemes with the average diversity combining, the theoretical bounds of throughput and bit error rate are derived, and it is shown that their bounds are tight and the treated schemes can attain a given error rate with good throughput for moderately time-varying channels. Furthermore, the throughput is shown to be improved by the partial retransmission scheme compared with the whole retransmission scheme.

We propose an asymmetric neural network which can solve inequality-constrained combinatorial optimization problems that are difficult to solve using symmetric neural networks. In this article, a knapsack problem that is one of such the problem is solved using the proposed network. Additionally, we study condition for obtaining a valid solution. In computer simulations, we show that the condition is correct and that the proposed network produces better solutions than the simple greedy algorithm.

The blazing effects of dielectric grating consisting of two adjacent sinusoidally modulated layers which lead to the asymmetric profiles on a substrate are analyzed by using improved Fourier series expansion method. This method can be applied to the wide range of grating structure and gave high accurate results by comparing with those obtained by previous method. In this paper, the efficient blazing effects can be achieved by varying normalized distance (w/p) and the normalized thickness (d1/D), where D is kept fixed. The results are greater than those of trapezoidal profiles and triangular profiles. The influences of the second order of modulation index on the radiation efficiencies and normalized leakage factor are also discussed.

In this report, we propose a robust block adaptive digital filter (BADF) which can improve the accuracy of the estimated weights by averaging the adaptive weight vectors. We show that the improvement of the estimated weights is independent of the input signal correlation.

In this paper, we demonstrate how Yamakawa's chaotic chips and Chua's circuits can be used to implement a secure communication system. Furthermore, their performance for the secure communication is discussed.

A 3-dimensional specific thickness profile was fabricated on a thin glass diaphragm lens to reduce aberration at short focal distances for greater dynamic focusing. The deformation of the diaphragm was calculated by stress analysis utilizing the Finite Element Method (FEM). Geometric non linearity is considered in the FEM analysis. The glass diaphragm is 10 mm in diameter and the average thickness is 11 µm. To obtain both a curved shape and an optical surface on the glass diaphragm, the 3-dimensional precision grinding technique was utilized. The processed shape matches the designed one with less than 0.3 µm deviation, and the average surface roughness is 0.005 µm. Optical characteristics of the dynamic focusing lens having a specific thickness profile, were measured by Modulation Transfer Function (MTF) measurement equipment. At a focal distance of 250 mm, the specific thickness diaphragm lens resolution is 10 cycles/mm, whereas, the uniform thickness diaphragm is 4 cycles/mm. Even at other focal distances, the specific thickness diaphragm shows superior optical characteristics in comparison with those of the uniform thickness diaphragm. The 3-dimensional profile diaphragm resolution is 2.5 times finer at a focal distance of 250 mm, thus, being capable of displacement control for variable optic devices. This was achieved by employing semiconductor processing methods in conjunction with precision grinding techniques which are necessary for fabricating micro structures.

A new electrostatic wobble motor design and fabrication method were proposed, and micromotors were successfully fabricated and operated. The advantages are (1) thicker structural size, resulting in larger torque, (2) simple and safe fabrication process and (3) needle-shaped bearing to support the rotor. Needle-shaped bearing used here is expected to have lower friction comparing with the existing motor, since the load is smaller for this kind of bearing structure. Two major sources of the load, electrostatic force and capillary force, were considered to prove this tendency. Diamond-like Carbon (DLC) film was employed as a solid lubricant for its bearing. The friction of DLC and that of ilicon-dioxide were compared by experiment.

This paper describes the method of applying the integral form of Maxwell's equations to the transmission-line network used in the spatial network method for the modeling of curved conductor surfaces. The techniques of dealing with the transmission-line network near cylindrical conductor surface are explained in detail. To compare exact solutions with computed values, a cylindrical cavity resonator is analysed. The resonant frequencies and unloaded Q's for the computed three modes are obtained with the error of about 1%. Moreover, applying this treatment to the waveguide with magnetron anodeshape cross section, a cutoff-constant is computed successfully. It is found that the treatment proposed in this paper can be used as the method for modeling of curved conductor surface in the spatial network method. It is also considered that this treatment can be extend to TLM method.

On mutually coupling lines, the transmission signal is dispersively propagated by crosstalk coupling between lines and shows complex propagation characteristics caused by reciprocal reflections. Usually, the differential equation and the integral equation have been applied to analyze the solutions of transmission lines. In this paper, we propose a different analytical method of the propagation characteristics of signal and crosstalk noise. By setting up crosstalk coupling line as a sectionally divided digital transmission network and by using the signal flow graph and the difference equation, the propagation characteristics in the frequency domain, the space domain and the time domain on mutually coupling lines can be obtained. To verify the validity of this method and analyze the complex propagation problems, we first study the crosstalk characteristics of a twisted pair cable via the third circuit by unidirectional coupling. Subsequently we will analyze the coupling theory of bidirectional coupling lines.

This letter proposes a time varying step size normalized LMS (TVS-NLMS) algorithm for adaptive echo canceler structures. Proposed algorithm reduces distortion during double talk, without increasing the computational cost nor decreasing the convergence rate of the normalized LMS algorithm significantly. Simulation results using white noise and actual speech signals confirm the desirable features of the proposed scheme.

This paper describes an advanced rule-embedded neural network (RENN+) that has an extended framework for achieving a very tight integration of learning-based neural networks and rule-bases of existing if-then rules. The RENN+ is effective in pattern recognition with ill-posed conditions. It is basically composed of several component RENNs and an output RENN, which are three-layer back-propagation (BP) networks except for the input layer. Each RENN can be pre-organized by embedding the if-then rules through translation of the rules into logic functions in a disjunctive normal form, and can be trainded to acquire adaptive rules as required. A weight-modification-reduced learning algorithm (WMR) capable of standard regularization is used for the post-training to suppress excessive modification of the weights for the embedded rules. To estimate the effectiveness of the proposed RENN+, it was used for pattern recognition in a radar system for detection of buried pipes. This trial showed that a RENN+ with two component RENNs had good recognition capability, whereas a conventional BP network was ineffective.

Recognition of hand drawn shapes is beneficial in drawing packages and automated sketch entry in hand-held computers. Although it is possible to store and retrieve drawings through the use of electronic ink, further manipulation of these drawings require recognition to be performed. In this paper, we propose a new approach to invariant geometric shape recognition which utilizes a fuzzy function to reduce noise and a neural network for classification. Instead of recognizing segments of a drawing and then performing syntactical analysis to match with a predefined shape, which is weak in terms of generalization and dealing with noise, we examine the shape as a whole. The main concept of the recognition method is derived from the fact that internal angles are very important in the perception of the shape. Our application's aim is to recognize and correctively redraw hand drawn ellipses, circles, rectangles, squares and triangles. The neural network learns the relationships between the internal angles of a shape and its classification, therefore only a few training samples which represent the class of the shape is sufficient. The results are very successful, such that the neural network correctly classified shapes which were not included in the training set.

In this paper, a new off-line handwritten word recognition method based on the explicit modeling of character junctures is presented. A handwritten word is regarded as a sequence of characters and junctures of four types. Hence both characters and junctures are explicitly modeled. A handwriting system employing hidden Markov models as the main statistical framework has been developed based on this scheme. An interconnection network of character and ligature models is constructed to model words of indefinite length. This model can ideally describe any form of hamdwritten words including discretely spaced words, pure cursive words, and unconstrained words of mixed styles. Also presented are efficient encoding and decoding schemes suitable for this model. The system has shown encouraging performance with a standard USPS database.