The newly developed high speed DRAMs are introduced and their innovative circuit techniques for achieving a high data bandwidth are described; the synchronous DRAM, the cache DRAM and the Rambus DRAM. They are all designed to fill the performance gap between MPUs and the main memory of computer systems, which will diverge in '90s. Although these high speed DRAMs have the same purpose to increase the data bandwidth, their approaches to accomplish it is different, which may in turn lead to some advantages or disadvantages as well as their fields of applications. The paper is intended not only to discuss them from technical overview, but also to be a guide to DRAM users when choosing the best fitting one for their systems.

Recent achievements in low-voltage and low-power circuit techniques are reported in this paper. DC current in low-voltage CMOS circuits stemming from the subthreshold current in MOS transistors, is effectively reduced by applying switched-power-line schemes. The AC current charging the capacitance in DRAM memory arrays is reduced by a partial activation of array blocks during the active mode and by a charge recycle during the refresh mode. A very-low-power reference-voltage generator is also reported to control the internal chip voltage precisely. These techniques will open the way to using giga-scale LSIs in battery-operated portable equipment.

We present an 8-dimensional trellis-coded 8-PSK with a symbol transition constraint that is similar to that of π/4-shift quadrature phase shift keying (QPSK). This scheme can achieve a coding gain of 1.6 to 2.4 dB at the same rate of π/4-shift QPSK on Gaussian channel, and it has also an immunity against the integer multiples of 90 phase ambiguities. In order to label the constellation of the proposed scheme, a constellation partitioning algorithm is presented. This algorithm, on the basis of set partitioning, can be used to label the signal constellation with no coset structure.

This paper proposes RSA-type cryptosystems over elliptic curves En(O, b) and En(a, O),where En(a, b): y2 x3+ax+b (mod n),and n is a product of from-free primes p and q. Although RSA cryptosystem is not secure against a low exponent attack, RSA-type cryptosystems over elliptic curves seems secure against a low multiplier attack. There are the KMOV cryptosystem and the Demytko cryptosystem that were previously proposed as RSA-type cryptosystems over elliptic curves. The KMOV cryptosystem uses form-restricted primes as p q 2(mod 3)or p q 3(mod 4), and encrypts/decrypts a 2log n-bit message over varied elliptic curves by operating values of x and y coordinates. The Demytko cryptosystem, which is an extension of the KMOV cryptosystem, uses form-free primes, and encrypts/decrypts a log n-bit message over fixed elliptic curves by operating only a value of x coordinates. Our cryptosystems, which are other extensions fo the KMOV cryptosystem, encrypt/decrypt a 2log n-bit message over varied elliptic curves by operating values of x and y coordinates. The Demytko cryptosystem and our cryptosystems have higher security than the KMOV cryptosystem because from-free primes hide two-bit information about prime factors. The encryption/decryption speed in one of our cryptosystems is about 1.25 times faster than that in the Demytko cryptosystem.

In computer vision, the interpretation of 3D motion of an object in the physical world is an important task. This study proposes a 3D motion interpretation method which uses a neural network system consisting of three kinds of neural networks. This system estimates the solutions of 3D motion of an object by interpreting three optical flow (OF-motion vector field calculated from images) patterns obtained at the different view points for the same object. In the system, OF normalization network is used to normalize diverse OF patterns into the normalized OF format. Then 2D motion interpretation network is used to interpret the normalized OF pattern and to obtain the object's projected motion onto an image plane. Finally, 3D motion interpretation network totally interprets the three sets of the projected motions and it derives the solutions of the object's 3D motion from the inputs. A complex numbered version of the back-propagation (Complex-BP) algorithm is applied to OF normalization netwerk and to 2D motion interpretation network, so that these networks can learn graphical patterns as complex numbers. Also a 3D vector version of the back-propagation (3DV-BP) algorithm is applied to 3D motion interpretation network so that the network can learn the spatial relationship between the object's 3D motion and the corresponding three OF patterns. Though the interpretation system is trained for only basic 3D motions consisting of a single motion component, the system can interpret unknown multiple 3D motions consisting of several motion components. The generalization capacity of the proposed system was confirmed using diverse test patterns. Also the robustness of the system to noise was probed experimentally. The experimental results showed that this method has suitable features for applying to real images.

In this paper, the Pisarenko and the Constrained Yule-Walker (CYW) estimators of a tone frequency are first newly derived from the viewpoint of using directly the autocorrelation coefficients. Then, simulation of these two estimators is carried out in some detail. The simulation results show that compared with the Pisarenko estimator the CYW estimator, which has not been adequately studied, works poorly for low and moderate Signal-to-Noise Ratio (SNR) values. However, in case of high SNR value, it yields very small bias and comparable estimation variance, and thus produces more accurate tone frequency estimates.

We have fabricated Nb/AlOx/Nb Josephson tunnel junctions by a sputtering apparatus with a load-lock system. This sputtering apparatus had the sub chamber for preparation and the main chamber for sputtering. The substrate temperature was confirmed to be kept less than 85 during Nb sputtering at the deposition rate of 1.18 nm/s for 7 minutes. The junctions that had 50µm50 µm area successfully showed the Vm value (the product of the critical current and the subgap resistance at 2 mV) as high as 50 mV at the current density of 100 A/cm2.

The magnitude of low frequency noise is studied in a Nb-(nanoconstrictions)-NbN system with adjustable current-voltage characteristics. We find that the magnitude of low frequency noise decreases sharply with increasing the subgap conductivity of the device. We suggest a qualitative explanation of this observation in terms of gradual build up of the nanoconstriction region by field assisted growth. The decrease of low frequency noise is related to the "cleanliness" of the system as measured by the amount of Andreev reflection-related conductivity. The scaling of the magnitude of low frequency noise with device resistance is also discussed.

We have systematically grown and characterized (Bi, Pb)2Sr2CaCu2Oy (BPSCCO) single crystals, and investigated the tunneling properties and the intrinsic Josephson effects of the single crystals as a function of the nominal composition of Pb, x. It was observed that Pb atoms (ions) were monotonically substituted for Bi atoms (ions) in the (Bi, Pb)-O layers of the crystals with increasing x in a region of 0x0.5, while the modulation structure was maintained in a range of 0x0.3, but disappeared in x0.3, accompanying the decrease of c-lattice parameter and Tc. Moreover, it was found that the energy gaps Δ of BPSCCO depend hardly on x for x0.5, which are about 24 meV, so that the Pb-induced electronic change in the (Bi, Pb)-O layer do not perturb the electronic states in this superconducting system. And it was confirmed that the currentvoltage characteristics of the BPSCCO single crystals had multiple resistive branches corresponding to a series array of several hundreds Josephson junctions, and showed Shapiro steps and zero-crossing steps with the voltage separation of the order of mV resulting from the phase locking of about a hundred Josephson junctions among them under microwave irradiation. The estimated number of junctions gave the concept that the intrinsic Josephson junctions consist of the superconducting block layers and the insulating layers in the BPSCCO single crystals.

High temperature superconductors are eminently suitable for use in high frequency devices because of their large energy gap. We fabricated weak link Josephson junctions connected in series. The junctions were constructed of EuBa2Cu3O7-x (EBCO) superconducting thin films on bicrystal MgO substrates. We measured their microwave broadband detection (video detection) characteristics. The responsivity (Sr) of the junctions depended on the bias current and their normal state resistance. The array junctions were effective in increasing normal state resistance. We obtained a maximum Sr of 22.6 [V/W].

This paper presents new go-back-N ARQ protocols for point-to-multipoint communications over broadcast channels such as satellite or broadcast radio channels. In the conventional go-back-N ARQ protocols for multidestination communications, usually only error detection codes are used for error detection and m copies of a frame are transmitted at a time. In one of our protocols, a bit-by-bit majority-voting decoder based on all of the m copies of a frame is used to recover the transmitted frame. In another protocol, a hybrid-ARQ protocol, which is an error detection code concatenated with a rate repetition convolutional code with the Viterbi decoding, is used. In these protocols, a dynamic programming technique is used to select the optimal number of copies of a frame to be transmitted at a time. The optimal number is determined by round trip propagation delay of the channel, the error probability, and the number of receivers that have not yet received the message. Analytic expressions are derived for the throughput efficiency of the proposed protocols. The proposed point-to-multipoint protocols provide satisfactory throughput efficiency and perform considerably better than the conventional protocols under high error rate conditions, especially in environments with a large number of receivers and large link round trips. In this paper we analyze the performances of the proposed protocols upon the random error channel conditions.

Linear lightwave networks (LLNs) are optical networks in which network nodes perform only linear operations on optical signals: power splitting, combining, and non-regenerative amplification. While previous efforts on LLNs assume only one fiber per link, we consider a multi-fiber linear lightwave network (M-LLN) architecture for telecommunications where switching exchanges are normally connected by multi-fiber cables. We propose a class of linear path (LP) allocation schemes for establishing optical paths in M-LLNs, and show that they have a better performance than those proposed for single-fiber LLNs. We show that M-LLNs can be implemented with commercially available components, and discuss the implementation issues in detail.

This paper presents a new line extraction method to capture vectors based on contours and skeletons from line drawing raster images in which the lines are touched by characters or other lines. Conventionally, two line extraction methods have generally been used. One is a thinning method. The other is a medial line extraction method based on parallel pairs of contours. The thinning method tends to distort the extracted lines, especially at intersections and corners. On the other hand, the medial line extraction method has a poor capability as regards capturing correct lines at intersections. Contours are able to maintain edge shapes well, while skeletons preserve topological features; thus, a combination of these features effectively leads to the best fitting line. In the proposed method, the line which best fits the original image is selected from among various candidate lines. The candidates are created from several merged short skeleton fragments located between pairs of short contour fragments. The method is also extended to circular arc fitting. Experimental results show that the proposed line fitting method is effective.

The demand for mobile communication services is rapidly increasing, because the mobile communication service is synonymy of an ideal communication style realizing communication in anytime, anywhere and with anyone. The development of economic and social activities is a primary factor of the increasing demand for mobile communication services. The demand stimulates the development of technology in mobile communication including personal communication services. Thus mobile communication has been one of the most active research in communications in the last several years. There exist various problems to which graph & network theory is applicable in mobile communication services (for example, channel assignment algorithm in cellular system, protocol in modile communication networks and traffic control in mobile communication ). A model of a cellular system has been formulated using a graph and it is known that the channel assignment problem is equivalent to the coloring problem of graph theory. Recently, two types of coloring problems on graphs or networks related to the channel assignment problem were proposed. Mainly, we introduce these coloring problems and show some results on these problems in this paper.

This paper discusses a digital neuroprocessor named Quantizer Neuron Chip (QNC) employing the Quantizer Neuron model and two newly developed schemes; "concurrent processing of quantizer neuron" and "removal of ineffective calculations". QNC simulates neural networks named the Multi-Functional Layered Network (MFLN) with 64 output neurons, 4672 quantizer neurons and two million synaptic weights and can be used for character or image recognition and learning. The processing speed of the chip achieved 1.6 µseconds per output neuron for recognition and 20 million connections updated per second (MCUPS) for learning. In addition, QNC can execute multichip operation for increasing the size of networks. We applied QNC to handwritten numeral recognition and realized high speed recognition and learning. QNC is implemented in a 1.2 µm double metal CMOS with sea of gates' technology and contains 27,000 gates on a 10.9910.93 mm2 chip.

This paper proposes a new burst coherent demodulator that improves transmission quality of microcellular TDMA/TDD systems for personal communications and has configuration suitable for low power consumption with LSIC-implementation. To achieve the better transmission quality, the proposed demodulator employs coherent detection with a unique carrier recovery scheme that can operate without any preamble for carrier recovery. In addition, the demodulator uses a clock recovery scheme with clock phase estimation using twice differentiation, which eliminates hangup and attains fast clock acquisition at 2 samples/symbol. Experimental results clarify the superiority of the proposed coherent demodulator for microcellular TDMA/TDD systems. The proposed coherent demodulator reduces the irreducible frame error rate by 40%, and achieves 4dB improvement at the frame error rate of 10% compared with differential detection under the Rayleigh fading (fD/fs=810-5, τrms/Ts=510-2) typical of personal communication environments.

The issue about document structure recognition and document understanding is today one of interesting subjects from a viewpoint of practical applications. The research objective is to extract the meaningful data from document images interpretatively and also classify them as the predefined item data automatically. In comparison with the traditional image-processing-based approaches, the knowledge-based approaches, which make use of various knowledge in order to interpret structural/constructive features of documents, have been currently investigated as more flexible and applicable methods. In this paper, we propose a totally integrated paradigm for understanding table-form documents from a viewpoint of the architectural framework.

We study robot navigation in unknown environment with rectangular obstacles aligned with the x and y axes. We propose a strategy called the modified-bian heuristic, and analyze its efficiency. Let n be the distance between the start point and the target of robot navigation, and let k be the maximum side length among the obstacles in a scene. We show that if k=(o(n) and if the summation of the widths of the obstacles on the line crossing the target and along the y axis is o(n), then ratio of the total distance walked by the robot to the shortest path length between the start point and the target is at most arbitrarily close to 1+k/2, as n grows. For the same restrictions as above on the sizes of the obstacles, the ratio is also at most arbitrarily close to 1+3/4n, as n grows, where is the summation of lengths of the obstacles in y axis direction.

An efficient algorithm is presented for solving nonlinear resistive networks. In this algorithm, the techniques of the piecewise-linear homotopy method are introduced to the Katzenelson algorithm, which is known to be globally convergent for a broad class of piecewise-linear resistive networks. The proposed algorithm has the following advantages over the original Katzenelson algorithm. First, it can be applied directly to nonlinear (not piecewise-linear) network equations. Secondly, it can find the accurate solutions of the nonlinear network equations with quadratic convergence. Therefore, accurate solutions can be computed efficiently without the piecewise-linear modeling process. The proposed algorithm is practically more advantageous than the piecewise-linear homotopy method because it is based on the Katzenelson algorithm that is very popular in circuit simulation and has been implemented on several circuit simulators.

This paper discusses the role of knowledge in document image understanding from the viewpoints of representation, utilization and acquisition. For the representation of knowledge, we propose two models, a layout model and a content model, which represent knowledge about the layout structure and content of a document, respectively. For the utilization of knowledge, we implement layout analysis and content analysis which utilize a layout model and a content model, respectively. The strategy of hypothesis generation and verification is introduced in order to integrate these two kinds of analysis. For the acquisition of knowledge, we propose a method of incremental acquisition of a layout model from a stream of example documents. From the experimental results of document image understanding and knowledge acquisition using 50 samples of visiting cards, we verified the effectiveness of the proposed method.