The DSD (Double Soft Decision) concatenated forward error correction scheme is proposed to realize a higher-coding-gain forward error correction system with simple hardware. The novel scheme soft decision decodes inner codes as well as outer codes. In this scheme, likelihood information from an inner Viterbi decoder is used for the decoding of outer codes. Path memory circuit status 1,0 ratio is newly proposed as a measure of likelihood information and it is shown that this method is the most reliable even though it has the simplest hardware among the alternative likelihood information extracting methods. Computer simulation clarifies that the proposed DSD scheme improves Pe performance to one-third that of the conventional hard decision outer decoding.

Among the many fabrication methods for oxide superconductor films, metal organic chemical vapor deposition (MOCVD) is particularly suitable for industrial application because of its mass productivity and the low growth temperature. Therefore we have studied this technique using the horizontal cold wall furnace type MOCVD method to obtain high quality superconducting films. As the result, we have succeeded in fabricating YBa2Cu3Oy films which have high critical temperatures (over 80 K) under substrate temperatures as low as 700 without post-annealing. But, in the course of our experiments, it was found that the thicknesses of YBa2Cu3Oy films fabricated by MOCVD were not uniform. The cause of this non-uniformity is believed to be that the deposition rate exponentially falls off along the flow direction because of the decrease of the source gas concentration through the reaction. In this paper, this non-uniformity is analytically studied. It is shown that the deposition rate decrease can be controlled with a tapered inner tube, and that these theoretical results are in good agreement with the results of experiment. In addition, it is indicated that the superconducting property of the films has less dependence on substrate position as a result of the tapered inner tube.

The wave distribution functions (WDFs) have been reconstructed by means of the maximum entropy inversion to the observed spectral matrix composed of the auto- and cross-power spectra among the three field components (Bx, By and Ez) in which the exactly right-handed circular polarization is taken in the integration kernels. The purpose of this paper is to investigate the properties of wave distribution functions reconstructed for wave sources whose central polarization is somewhat deviated from right-handed circular and to study (1) the WDF's by using the right-handed circular polarization in the kernels, (2) the effect of larger deviations for the polarization of elementary plane waves consituting the wave source, (3) the WDF's based on the elliptical polarization kernels and (4) the effect of limiting the number of eigenvalues. It is then found that changing the polarization model in the integration kernels would be helpful in finding out the polarization of the actually observed signals.

Bifurcations of the periodic solutions of the space-clamped Hodgkin-Huxley equations for the muscle membrane are studied regarding the chloride conductance as a parameter. A limit cycle appears at a Hopf bifurcation and disappears at a homoclinic orbit. With high sodium permeability, a subcritical period doubling bifurcation occurs before it disappears.

The single fault model is invalid in many cases. However, it is very difficult to generate tests for all multiple faults since an m-line circuit may have 3m --1 multiple faults. In this paper, we describe a method for generating tests for combinational circuits with multiple stuck-at faults. An input vector is a test for a fault on a target line, if it find the target line to be fault-free in the presence of undetected or undetectable lines. The test is called a robust test for fault on a target line. It is shown that the sensitizing input-pair for a completely single sensitized path can be a robust test-pair. The method described here consists of two procedures. We label these as SINGLE_SEN" procedure and DECISION" procedure. SINGLE_SEN generates a single sensitized path including a target line on it by using a PODEM-like method which uses a new seven-valued calculus. DECISION determines by utilizing the method proposed by H. Cox and J. Rajski whether the single sensitizing input-pair generated by the SINGLE_SEN is a robust test-pair. By using these two procedures the described method generates robust test-pairs for the combinational circuit with multiple stuck-at faults. Finally, we demonstrate by experimental results on the ISCAS85 benchmark circuits that SINGLE_SEN is effective for an algorithmic multiple fault test generation for circuits not including many XOR gates.

In general, a two-dimensional display is defined by two orthogonal unit vectors. In developing the display, discriminant analysis has a shortcoming that the extracted axes are not orthogonal in general. First, in order to overcome the shortcoming, we propose discriminant analysis which provides an orthonormal system in the transformed space. The transformation preserves the discriminatory ability in terms of the Fisher criterion. Second, we present a necessary and sufficient condition that discriminant analysis in the original space provides an orthonormal system. Finally, we investigate the relationship between orthogonal discriminant analysis and the Karhunen-Loeve expansion in the original space.

This paper deals with the problem of translating Japanese adnominal particles into English according to the idea of Example-Based Machine Translation (EBMT) proposed by Nagao. Japanese adnominal particles are important because: (1) they are frequent function words; (2) to translate them into English is difficult because their translations are diversified; (3) EBMT's effectiveness for adnominal particles suggests that EBMT is effective for other function words, e. g., prepositions of European languages. In EBMT, (1) a database which consists of examples (pairs of a source language expression and its target language translation) is prepared as knowledge for translation; (2) an example whose source expression is similar to the input phrase or sentence is retrieved from the example database; (3) by replacements of corresponding words in the target expression of the retrieved example, the translation is obtained. The similarity in EBMT is computed by the summation of the distance between words multiplied by the weight of each word. The authors' method differs from preceding research in two important points: (1) the authors utilize a general thesaurus to compute the distance between words; (2) the authors propose a weight which changes for every input. The feasibility of our approach has been proven through experiments concerning success rate.

Chemical structures of native oxides formed during wet chemical treatments of silicon surfaces were investigated using X-ray Photoelectron Spectroscopy (XPS) and Fourier Transformed Infrared. Attenuated Total Reflection (FT-IR-ATR). It was found that the amounts of Si-H bonds in native oxide and at native oxide/ silicon interface are negligibly small in the case of native oxides formed in H2SO4-H2O2 solution. Based on this discovery, it was found that native oxides can be characterized by the amount of Si-H bonds in the native oxide and the combination of various wet chemical treatments with the treatment in NH4OH-H2O2-H2O solution results in the drastic decrease in the amount of Si-H bonds in the native oxides.

Thermal desorption spectroscopy (TDS) is applied to analyze the oxidation reactions of hydrogen-terminated Si(100) surfaces in both the heating and cooling processes after hydrogen desorption. The oxidation reaction of oxygen and water with a silicon surface after hydrogen desorption shows hysteresis in the heating and cooling processes. In the cooling process, oxidation finishes when the silicon surface is adequately oxidized to about a 10 thickness. Oxidation continues to occur at lower temperatures when the total volume of oxygen and water is too small to saturate the bare silicon surface. The reaction of water with silicon releases hydrogen at more than 500. Hydrogen does not adsorb on the silicon oxide surface. A trace amount of oxygen, less than 110-6 Torr, roughens the surface.

A new cleaning solution (FPM; HF-H2O2-H2O) was investigated in order to remove effectively metallic impurities on the silicon wafer surface. The removability of metallic impurities on the wafer surface and the concentrations of metallic impurities adsorbed on the wafer surface from each contaminated cleaning solution were compared between FPM and conventional cleaning solutions, such as HPM (HCl-H2O2-H2O), SPM (H2SO4-H2O2), DHF (HF-H2O) and APM (NH4OH-H2O2-H2O). This new cleaning solution had higher removability of metallic impurities than conventional ones. Adsorption of some kinds of metallic impurities onto the wafer surface was a serious problem for conventional cleaning solutions. This problem was solved by the use of FPM. FPM was important not only as a cleaning solution for metallic impurities, but also as an etchant. Furthemore, this new cleaning solution made possible to construct a simple cleaning system, because the concentrations of HF and H2O2 are good to be less than 1% for each, and it can be used at room temperature.

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)).

In the approximate learning model introduced by Valiant, it has been shown by Blumer et al. that an Occam algorithm is immediately a PAC-learning algorithm. An Occam algorithm is a polynomial time algorithm that produces, for any sequence of examples, a simple hypothesis consistent with the examples. So an Occam algorithm is thought of as a procedure that compresses information in the examples. Weakening the compressing ability of Occam algorithms, a notion of weak Occam algorithms is introduced and the relationship between weak Occam algorithms and PAC-learning algorithms is investigated. It is shown that although a weak Occam algorithm is immediately a (probably) consistent PAC-learning algorithm, the converse does not hold. On the other hand, we show how to construct a weak Occam algorithm from a PAC-learning algorithm under some natural conditions. This result implies the equivalence between the existence of a weak Occam algorithm and that of a PAC-learning algorithm. Since the weak Occam algorithms constructed from PAC-learning algorithms are deterministic, our result improves a result of Board and Pitt's that the existence of a PAC-learning algorithm is equivalent to that of a randomized Occam algorithm.

We investigate the relationship between two different notions of reducibility among prediction (learning) problems within the distribution-free learning model of Valiant (PAC learning model). The notions of reducibility we consider are the analogues for prediction problems of the many-one reducibility and of the Turing reducibility. The former is the notion of prediction preserving reducibility developed by Pitt and Warmuth, and its generalization. Concerning these two notions of reducibility, we show that there exist a pair of prediction problems A and B, whose membership problems are polynomial time solvable, such that A is reducible to B with respect to the Turing reducibility, but not with respect to the prediction preserving reducibility. We show this result by making use of the notion of a class of polynomially sparse variants of a concept representation class. We first show that any class A of polynomially sparse variants of another class B is reducible to B with respect to the Turing reducibility'. We then prove the existence of a prediction problem R and a class R of polynomially sparse variants of R, such that R does not reduce to R with respect to the prediction preserving reducibility.

In this letter, we consider a magnetic or optical recording system employing a concatenated code that consists of a runlength-limited (d, k) block code as an inner code and a byte-error-correcting code as an outer code. (d, k) means that any two consecutive ones in the code bit stream are separated by at least d zeros and by at most k zeros. The minimum separation d and the maximum separation k are imposed in order to reduce intersymbol interference and extract clock control from the received bit stream, respectively. This letter recommends to use as the outer code a unidirectional-byte-error-correcting code instead of an ordinary byte-error-correcting code. If we devise the mapping of the code symbols of the outer code onto the codewords of the inner code, we may improve the error performance. Examples of the mappings are described.

The introduction of Integrated Services Digital Networks (ISDNs) poses a variety of new questions on telecommunications network design and planning. Furthermore, the formulation of traditional network design and planning problems need to be revisited in the ISDN context. This paper presents an overview of the recent progress and new challenges in developing ISDN design and planning methodologies that exploit revolutionary new telecommunications technologies. It will cover some important issues for ISDN design and planning, and will concentrate on three issues that are of particular importance: Design of networks with digital information transfer capabilities, design of networks with advanced network/traffic control techniques, and use of reliability objectives for network design and planning.

A novel coding scheme using orthonormal wavelet transform is proposed. Various forms of transform coding and subband coding are first reviewed. Then a wavelet coding method is proposed adopting a new approach similar to the one used for transform coding. The approach differs to conventional ones which considers wavelet coding as a class of subband coding. Simulation work is carried out to evaluate the proposed coding method. Significant improvement is obtained in subjective quality, and some improvement is also obtained in signal to noise ratio. Wavelet coding is still in its early stage of development, but can be considered to be a promising technique for image coding.

Syntax-directed editors have several advantages in editing programs because programming is guided by the syntax and free from syntax errors. Nevertheless, they are less popular than text editiors. One of the reason is that they force a priori specified editing structures on the user and do not allow him to use his own structure. ACE (Algorithmically Customizable syntax-directed Editor) provides a solution for this problem by using a technique of machine learning; ACE has a special function of customizing the grammar algorithmically and interactively based on the learning method for grammars from examples and queries. The grammar used in the editor is customized through interaction with the user so that the user can edit his program in a more familiar structure. The customizing function has been implemented based on the methods for learning of context-free grammars from structural examples, for which the correctness and the efficiency are proved formally. This guarantees the soundness and the efficiency of customization. Furthermore, ACE can be used as an algorithmic and interactive tool to design grammars, which is required for several purposes such as compiler design and pretty-printer design.

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.

The elementary formal system (EFS, for short) is a kind of logic program which directly manipulates character strings. This paper outlines in brief the authors' studies on algorithmic learning theory developed in the framework of EFS's. We define two important classes of EFS's and a new hierarchy of various language classes. Then we discuss EFS's as logic programs. We show that EFS's form a good framework for inductive inference of languages by presenting model inference system for EFS's in Shapiro's sense. Using the framework we also show that inductive inference from positive data and PAC-learning are both much more powerful than they have been believed. We illustrate an application of our theoretical results to Molecular Biology.

Optimal static load balancing problems in open BCMP queueing networks with state-independent arrival and service rates are studied. Their examples include optimal static load balancing in distributed computer systems and static routing in communication networks. We refer to the load balancing policy of minimizing the overall mean response (or sojourn) time of a job as the overall optimal policy. We show the conditions that the solutions of the overall optimal policy satisfy and show that the policy uniquely determines the utilization of each service center, the mean delay for each class and each path class, etc., although the solution, the utilization for each class, the mean delay for all classes at each service center, etc., may not be unique. Then we give tha linear relations that characterize the set whose elements are the optimal solutions, and discuss the condition wherein the overall optimal policy has a unique solution. In parametric analysis and numerical calculation of optimal values of performance variables we must ensure whether they can be uniquely determined.