An integrated CAD/CAM system for MMIC development has been firstly realized, which consists of electron beam direct drawing, microwave circuit simulator, pattern generator and RF &DC on-wafer automatic measurement subsystems, connected through an Ethernet LAN. The system can develop not only new MMICs and their element devices, but also their accurate simulation models quickly and efficiently. Preliminary successful applications of this system have been demonstrated by DC-HFET with a 0.25 µm T-shaped gate electrode and MMIC low-noise amplifiers operating at X- and L-bands.

Novel, very small-size multilayer MMIC's using miniature microstrip lines on a thin dielectric film, as well as the features of the multilayer structure, are presented. Very narrow-width thin-film transmission lines, meander-like configurations, line crossovers, and vertical connections, which are effective for significant chip-size reduction and flexible layout, are realized and utilized in a 2.5-3 µmN-layer dielectric film structure. 180-degree and 90-degree hybrids and umltiport Wilkinson dividers, which are implemented in small areas of 0.1 mm2 and 1.7 mm2, are presented. Furthermore, layout flexibility in the multilayer structure is demonstrated by implementing distributed amplifiers into the layers.

In this paper, voltage-input current-output Membership Function Circuit (MFC) and Normalization Locked Loop (NLL) are proposed. They are useful building blocks for the current-mode analog fuzzy hardware. The voltage-input current-output MFC consists of one source coupled type Operational Transconductance Amplifier (OTA). The MFC is used in the input parts of the analog fuzzy hardware system. The fuzzy hardware system can execute the singleton fuzzy control algorithm. In the algorithm, the weighted average operation is processed. When the weighted average operation is directly realized by analog circuits, a divider must be implemented. Here, the NLL circuit, which can process the weighted average operation without the divider, is implemented using one source coupled type OTA. The proposed circuits were designed by using 2 µm CMOS design rules and its operations were confirmed using SPICE simulations.

A simple method is developed to analyze a bent waveguide, which is described in the cylindrical coordinate system. By means of this method based on the Galerkin method, the sampling spacing can be chosen arbitrarily and it is possible to treat narrow beams. In addition we introduce the absorber using the graded lossy material. As this lossy absorber can remove the radiation wave from the bend, so we can use the finite computational window. The lightwaves propagating in the uniform bend of the slab waveguide and of the nonlinear slab waveguide are demonstrated.

We propose the coherent subcarrier multiplexed (SCM) system with distributing local oscillator (LO) in local loop. The proposed system can realize multichannel transmission with one optical carrier by using the SCM technique and has no need to have LO at each station. Therefore the proposed system becomes cost-effective. The proposed SCM system uses bandpass filter to select a specific channel. We analyze CNR of the system with frequency-shift keying (FSK) in a multioctave configuration. First, the general expression of CNR is derived and is shown for the following parameters such as the number of channels, the position of station on the loop, and the number of stations on the loop. Second, optimal phase modulation (PM) index is derived, and the optimal CNR, minimum required power of lasers, and maximum number of stations that the proposed system can serve are shown by using it. Moreover CNR of the proposed system is compared with that of the system having LO at each station in local loop. It is shown that the proposed system can obtain good performance at the expense of slight increase of the output power of only two lasers at the central station. Therefore the proposed system is cost-effective and practical.

An intermediate-frequency-combining (IF-combining) polarization diversity using frequency conversion is proposed. The proposed diversity requires no phase controller as opposed to the conventional IF-combining diversity. It has been theoretically clarified that this diversity has polarization insensitive bit-error-rate (BER) characteristics. The effectiveness has been confirmed by experiments in which the sensitivity dependence on the polarization is suppressed to within 0.8dB and a stable 101km fiber transmission at 600Mbit/s is achieved.

This paper proposes a Mean-Separated and Normalized Vector Quantizer with edge-Adaptive Feedback estimation and variable bit rates (AFMSN-VQ). The basic idea of the AFMSN-VQ is to estimate the statistical parameters of each coding block from its previous coded blocks and then use the estimated parameters to normalize the coding block prior to vector quantization. The edge-adaptive feedback estimator utilizes the interblock correlations of edge connectivity and gray level continuity to accurately estimate the mean and standard deviation of the coding block. The rate-variable VQ is to diminish distortion nonuniformity among image blocks of different activities and to improve the reconstruction quality of edges and contours to which the human vision is sensitive. Simulation results show that up to 2.7dB SNR gain of the AFMSN-VQ over the non-adaptive FMSN-VQ and up to 2.2dB over the 1616 ADCT can be achieved at 0.2-1.0 bit/pixel. Furthermore, the AFMSN-VQ shows a comparable coding performance to ADCT-VQ and A-PE-VQ.

An investigation into the spatial properties of the motion compensation prediction error signal has been carried out to provide a better understanding of it and to model the spatial power spectrum of the error signal. To construct a theoretical model, the motion compensation prediction process is analyzed, including the interpolation process used for motion compensation with decimal place precision, in the horizontal and vertical directions separately, thereby deriving its statistical power gain function. Properties of the input processing system are also examined. Based on these analyses, this paper proposes a theoretical model of the error signal, clarifies its spatial properties that are distinctive of the interlace scanned picture signal, and collates the obtained data with the real picture, thereby verifying the validity of the model. This model is especially useful for the evaluation, selection and detailed designing of the coding techniques of the error signal.

A theoretical conjecture on fractal dimensions of a dendrite distribution in neural networks is presented on the basis of the dendrite tree model. It is shown that the fractal dimensions obtained by the model are consistent with the recent experimental data.

In recent years, the digitalization of transmission links, such as optical fibre cables, satellite links, and terrestrial microwave links, has been progressed rapidly in many countries. In addition, many types of digital studio equipment have been developed and TV programs can be produced or edited without any picture quality degradation by using such equipment, for example, digital VTR. A high-efficiency bit-reduction coding system is the most promising and effective means for this situation in terms of reducing the cost of digital transmission of TV programs with high picture quality. Considering this background, a new digital coding system has been developed, which makes it possible to transmit up to 4 NTSC TV programs simultaneously over a single DS3 45Mbps link including two high quality sound channels and one 64kbps ancillary data channel for each TV program. The principal bit-reduction technique employed is 2 dimensional intraframe WHT (Walsh Hadamard Transform) coding, which gives higher coding performance for composite TV signals than DCT (Discrete Cosine Transform) coding. In order to attain high picture quality at around 8Mbps for 4 channel transmission, a 3 dimensional adaptive quantization cube which reflects human visual perception sufficiently is employed in the intraframe WHT coding scheme. The hardware has been made compact like a home use VTR. In this paper, first, the algorithm of the coding scheme developed for the coding system is presented, and then the system configuration and its basic coding performance are described.

This paper describes a new evaluation technique for Si surfaces. A laser/microwave method using two lasers of different wavelengths for carrier injection is proposed to evaluate Si surfaces. With this evaluation system, the effect of impedance mismatching between the microwave probe and the Si wafer can be eliminated. These lasers used in this experiment are He-Ne (wavelength633 nm, penetration depth3 µm) and YAG lasers (wavelength1060 nm, penetration depth500 µm). Using a microwave probe, the amount of injected excess carriers can be detected. These carrier concentrations are mainly dependent on the condition of the surface, when carriers are excited by the He-Ne laser, and the condition of the bulk region, when carriers are excited by the YAG laser. We refer to microwave intensities detected by the He-Ne and YAG lasers as the surface-recombination-velocity-related microwave intensity (SRMI) and bulk-related microwave intensity (BRMI), respectively. We refer to the difference between SRMI and BRMI as relative SRMI (R-SRMI), which is closely related to the surface condition. A theoretical analysis is performed and several experiments are conducted to evaluate Si surfaces. It is found that the R-SRMI method is better suited to surface evaluation then conventional lifetime measurements, and that the rdliability and reproducibility of measurements are improved.

A new set of self-consistent linear equations is presented for the analysis of the startup characteristics of gyrotron oscillators with an open cavity consisting of weakly irregular waveguides. Numerical results on frequency detuning and oscillation starting current for a whispering-gallery-mode gyrotron are described in which these equations were utilized. Experiments for making a check on the effectiveness of the derived equations showed that they well express the operation of gyrotrons in comparison with the linear theory using an empty cavity field as the wave field.

Despite its potential to realize image communication at extremely low rates, model-based coding (analysis-synthesis coding) still has problems to be solved for any practical use. The main problems are the difficulty in modeling unknown objects and the presence of analysis errors. To cope with these difficulties, we incorporate waveform coding into model-based coding (model-based/waveform hybrid coding). The incorporated waveform coder can code unmodeled objects and cancel the artifacts caused by the analysis errors. From a different point of view, the performance of the practically used waveform coder can be improved by the incorporation of model-based coding. Since the model-based coder codes the modeled part of the image at extremely low rates, more bits can be allocated for the coding of the unmodeled region. In this paper, we present the basic concept of model-based/waveform hybrid coding. We develop a model-based/MC-DCT hybrid coding system designed to improve the performance of the practically used MC-DCT coder. Simulation results of the system show that this coding method is effective at very low transmission rates such as 16kb/s. Image transmission at such low rates is quite difficult for an MC-DCT coder without the contribution of the model-based coder.

The purpose of the present paper is to review a state of the art of nonlinear analysis with the self-validating numerical method. The self-validating numerics based method provides a tool for performing computer assisted proofs of nonlinear problems by taking the effect of rounding errors in numerical computations rigorously into account. First, Kantorovich's approach of a posteriori error estimation method is surveyed, which is based on his convergence theorem of Newton's method. Then, Urabe's approach for computer assisted existence proofs is likewise discussed. Based on his convergence theorem of the simplified Newton method, he treated practical nonlinear differential equations such as the Van der Pol equation ahd the Duffing equation, and proved the existence of their periodic and quasi-periodic solutions by the self-validating numerics. An approach of the author for generalization and abstraction of Urabe's method are also discribed to more general funcional equations. Furthermore, methods for rigorous estimation of rounding errors are surveyed. Interval analytic methods are discussed. Then an approach of the author which uses rational arithmetic is reviewed. Finally, approaches for computer assisted proofs of nonlinear problems are surveyed, which are based on the self-validating numerics.

The Batcher banyan network is well known as a non-blocking switching fabric. However, it is conflict free only when there is no packets for the same destination. To cope with the arbitrary combination of packets, an additional network or special control sequence which causes the increase of the hardware or performance degradation is required. A Batcher Double Omega network with Combining (BDOC) is an elegant solution of this problem. It consists of a Batcher sorter and two double sized Omega networks. Like in the Batcher banyan network, packets are sorted by the destination label in the Batcher sorter. In the first Omega network called the distributer, a packet is routed by a tag corresponding to the sum of the label at the output of the Batcher sorter and the destination label. In the second (Inverse) Omega network called the concentrator, the original destination label is used as the routing tag, and packets are routed without any conflict. The BDOC is useful for an interconnection network to connect processors and memory modules in multiprocessor. Unlike conventional multistage interconnection networks for multiprocessors, packets are transferred in a serial and synchronized manner. The simple structure of the switching element enables a high speed operation which reduces the latency caused by the serial communication. Using the pipelined circuit switching, the address and data packets share the same control signal, and the structure of the switching element is much simplified. Moreover, packets combining which avoids the hot spot contention is realized easily in the concentrator.

This paper deals with an adaptive credit assignment algorithm to select strategies having higher capabilities in the learning classifier system (LCS) based upon the genetic algorithm (GA). We emulate a kind of prizes and incentives employed in the economies with imperfect information. The compensation scheme provides an automatic adjustment in response to the changes in the environment, and a comfortable guideline to incorporate the constraints. The learning process in the LCS based on the GA is realized by combining a pair of most capable strategies (called classifiers) represented as the production rules to replace another less capable strategy in the similar manner to the genetic operation on chromosomes in organisms. In the conventional scheme of the learning classifier system, the capability s(k, t) (called strength) of a strategy k at time t is measured by only the suitableness to sense and recognize the environment. But, we also define and utilize the prizes and incentives obtained by employing the strategy, so as to increase s(k, t) if the classifier provide good rules, and some amount is subtracted if the classifier k violate the constraints. The new algorithm is applied to the portfolio management. As the simulation result shows, the net return of the portfolio management system surpasses the average return obtained in the American securities market. The result of the illustrative example is compared to the same system composed of the neural networks, and related problems are discussed.

The energy distribution and emission efficiency of electrons emitted from a superconductor-insulator-superconductor (SIS) junction have been investigated by numerical calculation adopting the free electron model. The emission efficiency of an SIS junction cold cathode was found to be about 0.3% of tunneling current flowing to the SIS junction when the energy gap voltage of superconductor was 20 meV, the work function of counter electrode 1 eV, the bias voltage 0.96 V, the thickness of the counter electrode 100 , the electric field strength between the plate and the counter electrode 106 V/m, and the relaxation time 0.01 ps. It is clear that the SIS junction cold cathode can emit electrons with sharper energy distributions at much the same efficiency as compared with a metal-insulator-metal (MIM) junction cold cathode.

Very high resolution images with more than 2,000*2.000 pels will play a very important role in a wide variety of applications of future multimedia communications ranging from electronic publishing to broadcasting. To make communication of very high resolution images practicable, we need to develop image coding techniques that can compress very high resolution images efficiently. Taking the channel capacity limitation of the future communication into consideration, the requisite compression ratio will be estimated to be at least 1/10 to 1/20 for color signals. Among existing image coding techniques, the sub-band coding technique is one of the most suitable techniques. With its applications to high-fidelity compression of very high resolution images, one of the major problem is how to encode high frequency sub-band signals. High frequency sub-band signals are well modeled as having approximately memoryless probability distribution, and hence the best way to solve this problem is to improve the quantization of high frequency sub-band signals. From the standpoint stated above, the work herein first compares three different scalor quantization schemes and improved permutation codes, which the authors have previously developed extending the concept of permutation codes, from the aspect of quantization performance for a memoryless probability distribution that well approximates the real statistical properties of high frequency sub-band signals, and thus demonstrates that at low coding rates improved permutation codes outperform the other scalor quatization schemes and that its superiority decreases as its coding rate increases. Moreover, from the results stated above, the work herein, develops a rate-adaptive quantization technique where the number of bits assigned to each subblock is determined according to the signal variance within the subblock and the proper quantization scheme is chosen from among different types of quantization schemes according to the allocated number of bits, and applies it to the high-fidelity encoding of sub-band signals of very high resolution images to demonstrate its usefulness.

Recently much attention has been devoted to the problem of translating a set of geometrical objects in a given direction, one at a time, without allowing collisions between the objects. This paper studies the translation problem in three dimensions on a set of c-oriented faces", that is, the faces whose bounding edges have a constant number c of orientations. We solve the problem in O(N log2 NK) time and O(N log N) space, where N is the total number of edges of the faces and K is the number of edge intersections in the projection plane. As an intermediate step, we also solve a problem related to ray-shooting. The algorithm for translating c-oriented faces finds uses in computer graphic systems.

Artificial neurons and neural networks have been shown to perform Principal Component Analysis (PCA) when gradient ascent learning rules are used, which are related to the constrained maximization of statistical objective functions. Due to their parallelism and adaptivity to input data, such algorithms and their implementations in neural networks are potentially useful in feature extraction and data compression. In the companion paper(9), two such learning rules were derived from two criteria, the Subspace Criterion and the Weighted Subspace Criterion. It was shown that the only solutions to the latter problem are dominant eigenvectors of the data covariance matrix, which are the basis vectors of PCA. It was suggested by a simulation that the corresponding learning algorithm converges to these eigenvectors. A homogeneous neural network implementation was proposed for the algorithm. The learning algorithm is analyzed here in detail and it is shown that it can be approximated by a continuous-time differential equation that is obtained by averaging. It is shown that the asymptotically stable limits of this differntial equation are the eigenvectors. The neural network learning algorithm is further extended to a case in which each neuron has a sigmoidal nonlinear feedback activity function. Then no parameters specific to each neuron are needed, and the learning rule is fully homogeneous.