We present a high performance AlGaAs/GaAs power HBT with very low thermal resistance for digital cellular phones. Device structure with emitter air-bridge is utilized and device layout is optimized to reduce thermal resistance based on three-dimensional thermal flow analysis, and in spite of a rather thick substrate (100 µm), which achieved a low thermal resistance of 23/W for a multi-finger (440 µm240 fingers) HBT. This 40 finger HBT achieved power added efficiency (PAE) of over 53%, 29.1 dBm output power (Pout) and high associated gain (Ga) of 13.5 dB with 50 kHz adjacent channel leakage power (Padj) of less than -48 dBc under a 948 MHz π/4-shifted QPSK modulation with 3.4 V emitter-collector voltage. We also investigated the difference of RF performance between two bias modes (constant base voltage and current), and found which mode is adequate for each stage in several stage power amplifier for the first time.

Characteristics of a distortion, gain and efficiency of a power amplifier grow worse extremely by different phases of the load reflection coefficient when load impedances of the power amplifier are far from 50 Ω. It was found that the value of the distortion, gain and efficiency showed the tradeoff behavior when the phase of the reflection coefficient was different in 180 degrees. Therefore we have proposed new two- and four-parallel unit power amplifiers combined in 90 degree and 45 degree different phases each in order to accomplish low distortion and high efficiency in wide range of load impedances without an isolator. We studied the power amplifiers by simulation based on experiments and realized an amplifier in that adjacent channel leakage power of π/4-DQPSK modulation (for Japan's digital cellular system) is less than -45 dBc and efficiency is over 45% in range of load VSWR less than 3.

This paper describes a concept of the quasioptical spatial power combining technique and its demonstration of active integrated antenna arrays with strong coupling as an actual example of high efficient combiner in high frequencies. Some configurations of the arrays such as a 3-element linear array and a 33 array are designed with a circuit and electromagnetic simulator. In order to predict the operating frequencies, large signal FET model parameters are determined from measured small signal S-parameters.

With the dramatic rise in the number of Internet users, the expansion of international corporate activity and the arrival of multimedia services, highly-competitive information and communication services are entering a period of severe global change. There is widespread recognition that as these changes take place, it is important to establish operation and management (O&M) that will enable "seamless" end-to-end communication services between any points on the earth. With worldwide trends moving toward automation, the study of automation of O&M is being energetically pursued. This paper describes the requirements for service O&M and gives an overview of the technology believed to be essential to achieve them. The progress of developments is also reported.

We have been studying on subthreshold characteristics of SOI (Silicon-On-Insulator) MOSFET's in terms of substrate bias dependence using a one-dimensional subthreshold device simulator based on Poisson equation in an SOI multilayer structure for estimating structural parameters of real devices. Here, we consider the quantum mechanical effects in the electron inversion layer of thin SOI MOSFET's, such as the two-dimensionally quantized electron states and transports, with a self-consistent solver of Poisson and Schrodinger equations and a mobility model by the relaxation time approximation. From results of simulations, we found a significant difference between this model and the classical model and concluded that the quantum mechanical effects need to be considered in analizing thin-film SOI devices.

This paper describes the design, fabrication, and performance of a GaAs FET linearizer with a large source inductance, focusing mainly on (a) a mechanism of positive gain and negative phase deviations for input power, (b) stability considerations, and (c) a dependence on load impedance. In addition, in an application to the linearized amplifier, it is shown that an improvement can be achieved for adjacent channel leakage power (ACP) and third order intermodulation distortion (IM3) with the use of the linearizer.

This paper presents a character recognition method based on a dynamic model, which can be applied to character patterns from both on-line and off-line input. Other similar attempts simply treat on-line patterns as off-line input, while this method makes use of the on-line input's characteristics by representing the time information of handwriting in the character pattern representations. Experiments were carried out on the Hiragana character set. Without non-linear normalization, this method achieved recognition rates of 92.3% for on-line input and 89.1% for off-line input. When non-linear normalization is used, there is an increase in performance for both types of input with on-line input achieving 94.5% and off-line input achieving 94.1%. The reason for the difference in the effectiveness of non-linear normalization on off-line and on-line patterns could be that while the method used for off-line input was an established and proved one, we used our own initial attempt at non-linear normalization for the on-line patterns. If the same level of effectiveness of non-linear normalization as off-line input is achieved on the on-line input, however, the recognition rate for on-line input again improves becoming 96.3%. Since only one standard pattern was used per category for the dictionary patterns, the above results show the promise of this method. This result shows the compatibility of this method to both on-line and off-line input, as well as its effective use of on-line input's characteristics. The effectiveness of this use of the time information is shown by using an actual example. The data also shows the need for a method of non-linear normalization which is more suitable for on-line input.

Cross talk in mode-division multiplexing system is studied. The mode patterns when the fiber is bent are observed in the experiment.

In this paper a cyclic place-timed controlled marked graph (PTCMG), which is an extended class of a cyclic controlled marked graph (CMG), is presented as a model of discrete event systems (DESs). In a PTCMG, time constraints are attached to places instead of transitions. The time required for a marked place to be marked again is represented in terms of time constraints attached to places. The times required for an unmarked place to be marked under various controls, are calculated. The necessary and sufficient condition for a current marking to be in the admissible marking set with respect to the given forbidden condition is provided, as is the necessary and sufficient condition for a current marking to be out of the admissible marking set with respect to the forbidden condition in one transition. A maximally permissive state feedback control is synthesized in a PTCMG to guarantee a larger admissible marking set than a CMG for most forbidden state problems. Practical applications are illustrated for a railroad crossing problem and an automated guided vehicle (AGV) coordination problem in a flexible manufacturing facility.

In recent years, fractal processes have played important roles in various application fields. Since a 1/f process possesses the statistical self-similarity, it is considered sa a main part of fractal signal modeling. On the other hand, noise reduction is often needed in real-world signal processing. Hence, we propose an enhancement algorithm for 1/f signal disturbed by white noise. The algorithm is based on constrained minimization in a wavelet domain: the power of 1/f signal distortion in the wavelet domain is minimized under a constraint that the power of residual noise in the wavelet domain is smaller than a threshold level. We solve this constrained minimization problem using a Lagrangian equation. We also consider a setting method of the Lagrange multiplier in the proposed algorithm. In addition, we will confirm that the proposed algorithm with this Lagrange multiplier setting method obtains better enhancement results than the conventional algorithm through computer simulations.

Scattering of a plane electromagnetic wave by a conducting wedge will be discussed. The former solution can not be applicable to all the transition regions when its parameter is constant. This study shows a new solution which consists of only one expression applicable to the shadow region, the illuminated region and the transition regions, and which has no parameter.

A neural network approach called the "Gradual Neural Network (GNN)" for the time slot assignment problem in the TDM multicast switching system is presented in this paper. The goal of this NP-complete problem is to find an assignment of packet transmission requests into a minimum number of time slots. A packet can be transmitted from one source to several destinations simultaneously by its replication. A time slot represents a switching configuration of the system with unit time for each packet transmission through an I/O line. The GNN consists of the binary neural network and the gradual expansion scheme. The binary neural network satisfies the constraints imposed on the system by solving the motion equation, whereas the gradual expansion scheme minimizes the number of required time slots by gradually expanding activated neurons. The performance is evaluated through simulations in practical size systems, where the GNN finds far better solutions than the best existing altorithm.

This paper discusses the relationships of two important program classes of linearly recursive programs, that is, decomposable programs and rule commutative programs. We prove that the decomposable programs are always rule commutative. Furthermore, the rule commutative programs that satisfy certain conditions are decomposable. These results are meaningful for integrating the related specified optimization algorithms.

From a sequence {ai}i0 over GF(p) with period pn-1 we can obtain another periodic sequence {i}i0 with period pn-2 by deleting one symbol at the end of each period. We will give the bounds (upper bound and lower bound) of linear complexity of {i}i0 as a typical example of instability of linear complexity. Derivation of the bounds are performed by using the relation of characteristic polynomials between {ai}i0 and {ai(j)}i0={ai+j}i0, jGF(p){0}. For a binary m-sequence {ai}i0 with period 2n-1, n-1 a prime, we will give the explicit formula for the characteristic polynomial of {i}i0.

To enhance fabrication yield for processor arrays, many reconfiguration schemes for replacing faulty processing elements (PE's) with spare PE's have been proposed. An array grid model based on single-track switches is one of such models. For this model, some algorithms for reconfiguring processor arrays have been proposed. However, any algorithm which can reconfigure the array, whenever the array is reconfigurable, has not been proposed as yet. This paper describes reconfiguration methods of processor arrays with faulty PE's. The methods use indirect replacements for reconfiguring arrays. First, we introduce a concept of fatal fault pattern, which makes an array unreconfigurable. Then, for the reconfiguration method with fixed spare arrangement, efficient spare arrangements are given by evaluating the probability of an occurring fatal fault pattern. Furher, we present reconfiguration algorithm with relocating spare. In the algorithm, fatal fault patterns are eliminated by relocating spare. Computer simulations show that the method has good performance of reconfiguration.

This paper proposes a prediction method for non-stationary time series data with time varying parameters. A modular structured type neural network is newly introduced for the purpose of grasping the changing property of time varying parameters. This modular structured neural network is constructed by the hierarchical combination of each neural network (NNT: Neural Network for Prediction of Time Series Data) and a neural network (NNW: Neural Network for Prediction of Weights). Next, we propose a reasonable method for determination of the length of the local stationary section by using the additive learning ability of neural networks. Finally, the validity and effectiveness of the proposed method are confirmed through simulation and actual experiments.

Users of computer communication systems and their requirements are rapidly increasing and changing. It is desirable to have a development method which helps to make small changes in a design of a system to obtain another system which satisfies new requirement changes. We propose a flexible synthesis method which adopts designers' requirement changes in formal protocol specifications designed in LOTOS.

This paper discribes a shared medium access control protocol for residential home and small business customer ATM network application with distributed high-speed multimedia services. This protocol offers global fairness for the whole network with a CG (Centralized Grant) signal and, at the same time, offers local fairness between nodes with DG (Distributed Grant) signals. The DG signal is only meaningful to the next neighboring node. The local fairness is kept between two nodes in distributed way, but this distributed local fairness helps to keep the global fairness. Because the DG signal is related to the passed DG signal from the neighbor node. This protocol is rather simple but shows high performance than the already announced protocols.

Conformance testing is to see if the protocol implementation conforms to its specification. A lot of test sequences have been developed for testing centers. Yet directly applying these test sequences to the simple testing system in laboratories suffers from the frequently-occurred synchronization problems. This paper proposes a new technique to disconnect a test sequence into segments based on their functions, and reconnects them into a new test sequence that simulates these functions yet suffers less from the synchronization problems.

We present a new method for the adaptive control of nonminimum phase continuous-time systems based on the pole-zero placement using approximate inverse systems to avoid the unstable pole-zero cancellations. Using this method effect of the unstable zeros cab be compensated approximately. We show how unstable pole-zoro cancellations can be avoided, and that this method has the advantage of being able to determine an approximate inverse system independently of the plant zeros. The proposed scheme uses only the available input and output data and the stability using approximate inverse systems is analyzed. Finally, the results of computer simulation are presented to illustrate the effectiveness of the proposed method.