A pattern is a finite string of constant symbols and variable symbols. The language of a pattern is the set of all strings obtained by substituting any nonnull constant string for each variable symbol in the pattern. The class of pattern languages was introduced by Angluin in 1979 as a concrete class which is inferable from positive data. In this paper, we consider the decision problem whether for given two patterns there is a containment relation between their languages, which was posed by Angluin and its decidability remains open. We give some sufficient conditions to make this problem decidable. We also introduce the notions of generalizations and minimal generalizations common to a set of patterns. We characterize the above open problem using the minimal generalization.

As part of Hitachi's development of clean semiconductor processing equipment, the Fluids Modeling Group of the Mechanical Engineering Research Laboratory is developing a computer model, CONTAMINATE, for simulating contamination of wafers in chemical vapor deposition (CVD) systems. CONTAMINATE is based on a 2D implementation of the SIMPLER algorithm for simulating convection/diffusion transport processes. The new model includes modules for simulating fluid flow, heat transfer, chemical reactions, and gas-phase formation and deposition of clusters and particles. CONTAMINATE outputs property fields and estimates of various film quality indices. Using CONTAMINATE we simulated a SiH4: O2: N2 gas mixture at 300 K flowing over a wafer heated to 700 K. System pressures were varied from 1-100 torr and SiH4 pressures from 0.1 to 10 torr. Deposition characteristics are in qualitative agreement with actual systems and are summarized as follows: (1) No particles larger than 0.1µm deposited for any of the conditions tested. (2) Film damage occurred above 10 torr, but no damage occurred below 10 torr. (3) Increasing SiH4 pressure at constant system pressure eliminated particle deposition because particles grew large enought that thermophoresis blocked particle diffusion. (4) Conformal deposition of featured surfaces was achieved only at 1 torr. (5) Film thickness variation over the diameter of the wafer was 15% at 100 torr, 3% at 10 torr, and 1% at 1 torr.

In this paper, a new description of a separable-denominator (S-D) two-dimensional (2-D) transfer matrix is proposed, and its realization is considered. Some of this problem had been considered for the transfer matrices whose elements are two-variables rational functions. We shall propose a 2-D transfer matrix whose inputs-outputs relation is represented by a ratio of two-variables polynomial matrices, and present an algorithm to obtain a 2-D state-space model from it. Next, it is shown that the description proposed in this paper is always minimally realizable. And, we shall present a method of obtaining the description proposed in this paper from a S-D 2-D rational transfer matrix.

Voyager Neptune radio science data were collected using three antennas on Earth on August 25, 1989. A parabolic antenna at Canberra, Australia, of 70 meter diameter received 2.3GHz and 8.4GHz carriers. The 64 meter parabolic antennas at Parkes. Australia and Usuda, Japan, received only the 8.4GHz and only the 2.3GHz carriers, respectively. It is necessary to reduce the frequency variation in the received signal carrier to extract accurate information on physically interesting objects such as Neptune's atmosphere, ionosphere, or the rings. After the frequency stabilization process, the frequency drift was reduced from 180Hz down to a maximum of 5Hz, making it possible to reduce the data bandwidth and, consequently, the data volume, by a factor of 30. The uncertainty of the signal frequency estimates were also reduced from 5 down to 510-3Hz/sec above the atmosphere, from 5 down to 0.5Hz/sec in the atmosphere, and from 50 down to 3Hz/sec at the beginning and the end of the atmospheric occultation. Much of the remaining uncertainty is due to scintillations in Neptune's atmosphere and cannot be reduced further. The estimates are thus meaningfully accurate and suitable for scientific analysis and coherent arraying of data from different antennas. Two results based on these estimates are shown: a preliminary temperature-pressure (T-p) profile of Neptune's atmosphere down to a pressure level of 2 bar computed using the Usuda 2.3GHz data, and a multipath phenomenon in the atmosphere seen in Canberra 8.4GHz data. Our T-p profile shows good agreement with the results presented by Lindal et al. within 1K below 100mbar pressure level, even though our result is based on an independent data set and processing. A comparison of the multipath phenomena at Neptune with that at Uranus implies that it was created by a cloud layer with a smaller scale height than the atmosphere above and below it. The processing methods described were developed in part with the interest to coherently array Canberra, Parkes and Usuda data. In this sense, while this paper does not extend any science results, the observations and results are derived independently from other published results, and in the case of Usuda, are completely new.

This paper describes a super high definition (SHD) image processing system we have developed. The computing engine of this system is a parallel processing system with 128 processing elements called NOVI- HiPIPE. A new pipelined vector processor is introduced as a backend processor of each processing element in order to meet the great computing power required by SHD image processing. This pipelined vector processor can achieve 120 MFLOPS. The 128 pipelined vector processors installed in NOVI- HiPIPE yield a total system peak performance of 15 GFLOPS. The SHD image processing system consists of an SHD image scanner, and SHD image storage node, a full color printer, a film recorder, NOVI- HiPIPE, and a Super Frame Memory. The Super Frame Memory can display a ful color moving image sequence at a rate of 60 fps on a CRT monitor at a resolution of 2048 by 2048 pixels. Workstations, interconnected through an Ethernet, are used to control these units, and SHD image data can be easily transfered among the units. NOVI- HiPIPE has a frame memory which can display SHD still images on a color monitor, therefore, one processed frame can be directly displayed. We are developing SHD image processing algorithms and parallel processing methodologies using this system.

This paper describes the application of a neural network to the optimal routing problem in broadband multimedia networks, where the objective is to maximize network utilization while considering the performance required for each call. In a multimedia environment, the performance required for each call is different, and an optimal path must be found whenever a call arrives. A neural network is appropriate for the computation of an optimal path, as it provides real-time solutions to difficult optimization problems. We formulated optimal routing based on the Hop field neural network model, and evaluated the basic behavior of neural networks. This evaluation confirmed the validity of the neural network formulation, which has a small computation time even if there are many nodes. This characteristic is especially suitable for a large-scale system. In addition, we performed a computer simulation of the proposed routing scheme and compared it with conventional alternate routing schemes. The results show the benefit of neural networks for the routing problem, as our scheme always balances the network load and attains high network utilization.

In this paper, we consider the polynomial time inferability from positive data for unions of two tree pattern languages. A tree pattern is a structured pattern known as a term in logic programming, and a tree pattern language is the set of all ground instances of a tree pattern. We present a polynomial time algorithm to find a minimal union of two tree pattern languages containing given examples. Our algorithm can be considered as a natural extension of Plotkin's least generalization algorithm, which finds a minimal single tree pattern language. By using this algorithm, we can realize a consistent and conservative polynomial time inference machine that identifies unions of two tree pattern languages from positive data in the limit.

This paper proposes a model for learning non-parametric densities using finite-dimensional parametric densities by applying Yamanishi's stochastic analogue of Valiant's probably approximately correct learning model to density estimation. The goal of our learning model is to find, with high probability, a good parametric approximation of the non-parametric target density with sample size and computation time polynomial in parameters of interest. We use a learning algorithm based on the minimum description length (MDL) principle and derive a new general upper bound on the rate of convergence of the MDL estimator to a true non-parametric density. On the basis of this result, we demonstrate polynomial-sample-size learnability of classes of non-parametric densities (defined under some smoothness conditions) in terms of exponential families with polynomial bases, and we prove that under some appropriate conditions, the sample complexity of learning them is bounded as O((1/ε)(2r1)/2r1n(2r1)/2r(1/ε)(1/ε)1n(1/δ) for a smoothness parameter r (a positive integer), where ε and δ are respectively accuracy and confidence parameters. Futher, we demonstrate polynomial-time learnability of classes of non-parametric densities (defined under some smoothness conditions) in terms of histogram densities with equal-length cells, and we prove that under some appropriate condition, the sample complexity of learning them is bounded as O((1/ε)3/21n3/2(1/ε)(1/ε)1n(1/δ)).

Spoken language systems such as speech-to-speech dialog translation systems have been gaining more attention in recent years. These systems require full integration of speech recognition and natural language understanding. This paper presents an efficient parsing algorithm that integrates the search problems of speech processing and language processing. The parsing algorithm we propose here is regarded as an extension of the finite-state-network directed, one-pass search algorithm to one directed by a context-free grammar with retention of the time-synchronous procedure. The extended search algorithm is used to find approximately globally optimal sentence hypotheses; it does not have overhead which exists in, for example, hierarchical systems based on the lattice parsing approach. The computational complexity of this search algorithm is proportional to the length of the input speech. As the search process in the speech recognition can directly take account of the predictive information in the sentence parsing, this framework can be extended to sopken language systems which deal with dynamically varying constraints in dialogue situations.

A new Elastic-Block Matching Algorithm using bilinear space warping is proposed. In this scheme a convex quadrilateral, which minimizes a distortion measure against the current square block, is searched to compensate the shape deformation caused by a rigid body's 3 dimensional depth motion or rotation. The proposed algorithm gives a remarkable improvement in motion-compensated prediction compared with the conventional algorithm.

User capacity of a DS/CDMA cellular mobile radio system employing transmitter power control (TPC) is investigated. Assuming log-normally distributed control error, outage probability is evaluated through computer simulations. The user capacity is dramatically decreased as the power control error increases. If the standard deviation is larger than about 2dB, the user capacity is decreased by more than 60%. It is shown that power control error with a standard deviation of less than or equal to 0.5dB is required to accommodate 90% of the maximum user capacity. The capacity decrease in the reverse and forward link channels due to non-uniform user distributions are also investigated. It is shown that if system users are densely distributed within the zone fringe whose thickness is 80% of the radius, the reverse link capacity is decreased by about 22%. The forward link capacity is comparatively insenstitive to non-uniform user distribution.

This paper analyzes the performance of the capacity controlled digital radio system, which controls the number of modulation levels according to the amount of traffic. These analyses are performed under thermal noise and co-channel interference. As a result, the throughput improvement is approximately 16 times comparing with the fixed capacity system which has the designed outage probability of 0.1%. Theoretical results are applied to the future mobile communication system which utilizes TDMA access method or burst co-dec, and it is found that the reuse distance can be improved to 1/5 times when the designed outage probability is 0.1%.

For a realization of a DC-DC converter using no magnetic devices, a new switched capacitor (SC) transformer is introduced, which gives voltage ratios by Fibonacci series corresponding to the stages. This transformer is connected in cascade by each basic block which is assembled by a capacitor and three MOSFET switches. This operates on a simple two-phase clock and has a large step-up or step-down voltage ratio in spite of its simple configuration. The characteristics of this transformer with n stages of basic block are derived and calculated by means of a 4 4 cascade matrix. The optimal arrangement of each stage's capacitances is shown to reduce the SC resistance by about 20%. The simulation results are compared with the characteristics of a prototype transformer with four stages (8 times step-up ratio). Its power efficiency achieves 88% in case of 97 V output voltage, 0.2 A output current, and 100 kHz switching frequency. Lastly, the proposed SC transformer is compared and discussed with other typical SC transformers.

This paper proposes parallel VLSI processors for robotics based on multiple processing elements organized around multiple bus interconnection networks. The advantages of multiple bus interconnection networks are generality, simplicity of implementation and capability of parallel communications between processing elements, therefore it is considered to be suitable for parallel VLSI systems. We also propose the optimal scheduling formulated in an integer programming problem to minimize the delay time of the parallel VLSI processors.

The optimal coding strategy for signal detection in the correlated gaussian noise is established for the distributed sensors system with essentially zero transmission rate constraint. Specifically, we are able to obtain the same performance as in the situation of no restriction on rate from each sensor terminal to the fusion center. This simple result contrasts with the previous ad hoc studies containing many unnatural assumptions such as the independence of noises contaminating received signal at each sensor. For the design of optimal coder, we can use the classical Levinson-Wiggins-Robinson fast algorithm for block Toeplitz matrix to evaluate the necessary weight vector for the maximum-likelihood detection.

The encoding of high quality and super high definition images requires new approaches to the coding problem. The nature of such images and the applications in which they are used prohibits the introduction of perceptible degradation by the coding process. In this paper, we discuss techniques for the perceptually transparent coding of images. Although technically lossy methods, images encoded and reconstructed using these techniques appear identical to the original images. The reconstructed images can be postprocessed (e.g., enhanced via anisotropic filtering), due to the absence of structured errors, commonly introduced by conventional lossy methods. The compression, ratios obtained are substantially higher than those achieved using lossless means.

This paper discusses the design, implementation, and performance of a bus-connected multiprocessor, called Presto, for a Rete-based production system. To perform a match, which is a major phase of a production system, a Presto match scheme exploits the subnetworks that are separated by the top two-input nodes and the token flow control at these nodes. Since parallelism of a production system can only increase speed 10-fold, the aim is to do so efficiently on a low-cost, compact bus-connected multi-processor system without shared memory or cache memory. The Presto hardware consists of up to 10 processisng elements (PEs), each comprising a commercial microprocessor, 4 Mbytes of local memory, and two kinds of newly developed ASIC chips for memory control and bus control. Hierarchical system software is provided for developing interpreter programs. Measurement with 10 PEs shows that sample programs run 5-7 times faster.

High-speed digital land mobile communications suffer from frequency-selective fading due to a long delay difference. Several techniques have been proposed to overcome the multipath propagation problem. Among them, an adaptive array antenna is suitable for very high-speed transmission because it can suppress the multipath signal of a long delay difference significantly. This paper describes the LMS adaptive array antenna for frequency-selective fading reduction and a new diversity technique. First, we propose a method to generate a reference signal in the LMS adaptive array. At the beginning of communication, we use training codes for the reference signal, which are known at a receiver. After the training period, we use detected codes for the reference signal. We can generate the reference signal modulating a carrier at the receiver by those codes. The carrier is oscillated independently of the incident signal. Then, the carrier frequency of the reference signal is in general different from that of the incident signal. However, the LMS adaptive array works in such a way that the carrier frequency of the array output coincides with that of the reference signal. Namely, the frequency difference does not affect the performance of the LMS adaptive array. Computer simulations show the proper behavior of the LMS adaptive array with the above reference signal generator. Moreover, we present a new multipath diversity technique using the LMS adaptive array. The LMS adaptive array reduces the frequency-selective fading by suppressing the multipath components. This means that the transmitted power is not used sufficiently. We propose a multiple beam antenna with the LMS adaptive array. Each antenna pattern receives one of the multipath components, and we combine them adjusting the timing. Then, we realize the multipath diversity. In addition to the multipath fading reduction, we can improve a signal-to-noise ratio by the diversity technique.

This paper reviews the capability of the three layer neural network (TLNN) with one output neuron. The input set is restricted to a finite subset S of En, and the TLNN implements a function F such as F : S I={1, -1}, i,e., F is a dichotomy of S. How many functions (dichotomies) can it compute by appropriately adjusting parameters in the TLNN? Brief historical review, some theorems on the subject obtained so far, and related topics are presented. Several open problems are also included.

This paper attempts to account for intelligibility of practices-based learning (so-called 'learning control') for skill refinement from the viewpoint of Newtonian mechanics. It is shown from an axiomatic approach that an extended notion of passivity for the residual error dynamics of robots plays a crucial role in their ability of learning. More precisely, it is shown that the exponentially weighted passivity with respect to residual velocity vector and torque vector leads the robot system to the convergence of trajectory tracking errors to zero with repeating practices. For a class of tasks when the endpoint is constrained geometrically on a surface, the problem of convergence of residual tracking errors and residual contact-force errors is also discussed on the basis of passivity analysis.