A new anti-static technology to neutralize static electricity by high energy photon irradiation has been developed. Ions and electrons required for neutralization are generated by ionization of gas molecules in the vicinity of a charged substance. Gas molecules absorbs photons to become ionized. The wavelength chosen for the irradiation depends on the neutralization atmosphere. Soft X-rays with wavelength over about 1 are effective in air or O2 gas at pressure higher than several hundreds Torr. Vacuum UV-rays with wavelength below about 1350 is effective in N2 gas, Ar gas, or reduced pressure ambients. These methods feature excellent neutralization capa-bility. Electrostatic potential can be reduced to 0 V in a very short time without encountering the problems of which conven-tional corona discharge ionizers.

This paper proposes a method for achieving low-power control-logic modules using a combination of CMOS complex gate reorganization, transistor size optimization, and transistor layout. Complex gate reorganization minimizes transistor count and net count without changing the functionality of the circuit. Transistor sizing and layout are interdependent, the optimization of one results in the optimization of the other. The authors applied the reorganization method to a 10,846-transistor circuit, and succeeded in reducing the transistor count by 10%, and the net count by 9%. Transistor sizing and layout compaction reduced the average transistor size by one tenth, while the same delay was maintained. Total circuit capacitance, which is strongly related to power dissipation, was cut to 36%, even when wiring capacitances were dominant.

This paper proposes a tool to analyze complicated phenomena from a simple hysteresis network. The simple hysteresis network is described by a piecewise liner ordinal differential equation and has only two parameters: self feedback and DC team. Then this simple system exhibits various kinds of attractors: stable equilibria, periodic orbits, tori and chaos. In order to perform the numerical analysis, we derive return map and propose a fast calculation algorithm for the return map and its Lyapunov exponents based on the exact solutions. Using this algorithm, we have clarified chaos generation and related bifurcation phenomena. Also, we give theoretical formula that give fundamental bifurcation set.

Understanding unknown objects in images is one of the most important fields of the computer vision. We are confronted with the problem of dealing with the ambiguity of the image information about unknown objects in the scene. The purpose of this paper is to propose a new object recognition method based on the fuzzy relation system and the fuzzy integral. In order to deal with the ambiguity of the image information, we apply the fuzzy theory to object recognition subjects. Firstly, we define the degree of similarity based on the fuzzy relation system among input images and object models. In the next, to avoid the uncertainty of relations between the input image and the 2-D aspects of models, we integrate the degree of similarity obtained from several input images by the fuzzy integral. This proposing method makes it possible to recognize the unknown objects correctly under the ambiguity of the image information. And the validity of our method is confirmed by the experiments with six kinds of chairs.

This paper describes Kleenean coefficients that are a subset of Kleenean functions for use in representing multiple-valued logic functions. A conventional multiple-valued sum-of-products expression uses product terms that are the MIN of literals and constants. In this paper, a new sum-of-products expression is allowed to sum product terms that also include variables and complements of variables. Since the conventional sum-of-products expression is complete, so also is the augmented one. A minimization method of the new expression is described besed on the binary Quine-McCluskey algorithm. The result of computer simulation shows that a saving of the number of implicants used in minimal expressions by approximately 9% on the average can be obtained for some random functions. A result for some arithmetic functions shows that the minimal solutions of MOD radix SUM, MAX and MIN functions require much fewer implicants than those of the standard sum-of-products expressions. Thus, this paper clarifies that the new expression has an advantage to reduce the number of implicants in minimal sum-of-products expressions.

The realization of scientific manufacturing of ULSIs in the 21st century will require the development of a technical infrastructure of "Ultra Clean Technology" and the firm establishment of the three principles of high performance processes. Three principles are 1)Ultra Clean Si Wafer Surface, 2)Ultra Clean Processing Environment, and 3)Perfect Parameter controlled process. This paper describes the methods of resolving the problems inherent in Ultra Clean Technology, taking as examples issues in quarter-micron or more advanced semiconductor process and manufacturing equipment, particularly when faced with the challenges of plasma dry etching. Issues indispensable to the development of tomorrow's highly accurate and reliable plasma dry etching equipment are the development of technologies for the accurate measurement of plasma parameters, ultra clean gas delivery systems, chamber cleaning technology on an in-situ basis, and simulating the plasma chemistry.This paper also discusses the standardization of semiconductor manufacturing equipment, which is considered one of the ways to reduce the steep rise in production line construction costs. The establishment of Ultra Clean Technology also plays a vital role in this regard.

This letter presents a new design method for approximate inverse systems using all-pass networks. The efficacy of approximate inverse systems for input and parameter estimation of nonminimum phase systems is well recognized. in the previous methods, only time domain design of FIR (finite impulse response) type approximate inverse systems were considered. Here, we demonstrate that IIR (infinite impulse response) type approximate inverse systems outperform the previous methods. A nonlinear optimization technique is adopted for designing the proposed system in the frequency domain. Numerical examples are also presented to show the effectiveness of the proposed method.

This paper proposes an integrated interference suppression scheme which realizes interference-resistant satellite digital signal transmission systems. It employs a notch filter in the receiving side to suppress the co-channel interference (CCI) signal. Moreover, the proposed scheme employs an adaptive equalizer combined with a forward error correction (FEC) scheme to improve the Pe (probability of error) performance degradation due to the inter-symbol interference caused by notch filtering of the desired signal. In the typical frequency modulation (FM) CCI environment with a BWi/FN of 2.3 (BWi: interference signal required bandwidth, fN: one half the Nyquist bandwidth of the desired signal), a Δf / fN of 1.05 (Δf: interference frequency offset) and a D/U of 3 dB (desired to undesired (interference) signal power ratio), the proposed scheme improves the required Eb/NO by 1.5 dB at a Pe of 10-4 compared to that without an adaptive equalizer.

This work addresses the problems of bit allocation and coding gain in subband coding system with non-paraunitary filter banks. Since energy conservation does not hold in non-paraunitary filter banks, the model to be adopted for quantizers is important to evaluate the output distortion introduced by subband signal quantization. To evaluate the overall distortion we start with adopting the gain plus additive noise model for quantizers, which is more reliable than the additive noise model. With this model, the expression for overall reconstruction error variance becomes so complicated that the problem of optimum bit allocation, as required for evaluation of the coding gain, must be numerically solved. So, we propose an approximation method in which we neglect the terms due to correlation among quantization errors in calculating the bit allocation but take them into consideration in evaluating the coding gain, assuming sufficiently high bitrate coding. Application of this approximation method to the SSKF subband coding systems with AR (1) input source shows that the method is very accurate even at low bit rate coding (1 bit/sample).

In this paper, we propose a new method of dialogue data collection which can be used to evaluate modules of a spoken dialogue system. To evaluate the module, it is necessary to use suitable data. Human-human dialogue data have not been appropriate to module evaluation, because spontaneous data usually include too much specific phenomena such as fillers, restarts, pauses, and hesitations. Human-machine dialogue data have not been appropriate to module evaluation, because the dialogue was unnatural and the available vocabularies were limited. Here, we propose 'Hybrid method' for the collection of spoken dialogue data. The merit is that, the collected data can be used as test data for the evaluation of a spoken dialogue system without any modification. In our method a human takes the role of some modules of the system and the system, also, works as the other part of the system together. For example, humans works as the speech recognition module and the dialogue management and a machine does the other part, response generation module. The collected data are good for the evaluation of the speech recognition and the dialogue management modules. The reasons are as follows. (1) Lexicon: The lexicon was composed of limited words and dependent on the task. (2) Grammar: The intention expressed by the subjects were concise and clear. (3) Topics: There were few utterances outside the task domain. The collected data can be used test data for the evaluation of a spoken dialogue system without any modification.

This paper proposes a novel optical modulator for a millimeter wave (MMW) subcarrier optic link. The modulator enables the bi-phase modulation of MMW subcarriers. It simplifies the optic link by unifying such functions as IF modulation, up-convertion to MMW, and optical modulation, which are separately equipped in a conventional system. A simple model of a Mach-Zehnder external optical modulator (EOM) is used to illustrate how bi-phase modulation of millimeter wave (MMW) subcarriers can be accomplished by switching the EOM bias with a binary data signal. Experimental results are presented to confirm predictions. A wideband communications test system employing the EOM as a bi-phase modulator and utilizing spread spectrum modulation (1.3 µm optical wavelength, 40 GHz subcarrier, 100 MHz chip rate, 10MHz data rate) was developed. Bit error rate (BER) characteristics of an optical link that includes the proposed modulator are presented and compared with ideal performance and simulated predictions. Degradation of the BER characteristics from the simulation was less than 1 dB at a BER of 10-6. A frequency doubling subcarrier bi-phase modulator is also described.

In this communication we propose to solve the problem of reconstruction from limited data using a statistical regularization method based on a Bayesian information criterion. The minimization of the Bayesian information criterion, which is used here as an objective index to measure the goodness of an estimate, gives the optimum value of the smoothing parameter. By doing so, we could reduce the inversion problem to a simple minimization of a one-variable nonlinear function. The application of such a technique overcomes the nonuniqueness of the solution of the ill-posed problem and all shortcomings of many iterative methods. In the light of simulation and application to real data, we propose a slight modification to the Bayesian information criterion to reconstruct the wave energy distribution at the ionospheric base from the observation of radio wave electromagnetic field on the ground. The achieved results in both the inversion problem and the wave direction finding are very promising and may support other works so far suggested the use of Bayesian methods in the inversion of ill-posed problems to benefit from the valuable information brought by the a priori knowledge.

This paper describes a finite element method to obtain an accurate solution of the scalar Helmholtz equation with field singularities. It is known that the spatial derivatives of the eigenfunction of the scalar Helmholtz equation become infinite under certain conditions. These field singularities under mine the accuracy of the numerical solutions obtained by conventional finite element methods based on piecewise polynomials. In this paper, a regularized eigenfunction is introduced by subtracting the field singularities from the original eigenfunction. The finite element method formulated in terms of the regularized eigenfunction is expected to improve the accuracy and convergence of the numerical solutions. The finite element matrices for the present method can be easily evaluated since they do not involve any singular integrands. Moreover, the Dirichlet-type boundary conditions are explicitly imposed on the variables using a transform matrix while the Neumann-type boundary conditions are implicitly imposed in the functional. The numerical results for three test problems show that the present method clearly improves the accuracy of the numerical solutions.

An optoelectronic beam forming network (BFN) is presented for a single beam, 3-element phased array antenna that utilizes electrically controllable birefringence mode nematic liquid-crystal cells (ECB mode NLC cells) for phase shifting and amplitude control. In the circuit, a microwave signal is carried by a pair of orthogonal linearly polarized lightwaves (signal and reference lightwaves) using the optical heterodyning technique. Birefringence of liquid-crystals is utilized to selectively control the phase of the signal and reference lightwaves. Because an interferometer is formed on a single signal path, the complexity of the optical circuit is much reduced, compared to the BFNs based on arrays of Mach-Zender interferometers. A prototype circuit is built using laser sources of 1.3 µm, and its performance experimentally examined. With small deviations among the three cells, phase shifts of up to 240 degrees are achived for MW signals from 0.9 GHz to 20 GHz with good stability; attenuation of more than 18dB is achieved. An optoelectronic technique for parallel control of amplitude and phase of MW signals was developed.

The present paper is concerned with an algorithm for the minimization of multiple-valued input, binary-valued output functions. The algorithm is an extension to muitiple-valued logic of an algorithm for the minimization of ordinary single-output Boolean functions. It is based on a local covering approach. Basically, it uses a "divide and conquer" technique, consisting of two steps called expansion and selection. The present algorithm preserves two important features of the original one. First, a lower bound on the number of prime implicants in the minimum cover of the given function is furnished as a by-product of the minimization. Second, all the essential primes of the function are identified and selected during the expansion process. That usually improves efficiency when handling functions with many essential primes. Results of a comparison of the proposed algorithm with the program ESPRESSO-IIC developed at Berkeley are presented.

In previous papers the building of hierarchical networks made up of components using fuzzy rules was presented. It was demonstrated that this approach could be used to construct networks to solve classification problems, and that in many cases these networks were computationally less expensive and performed at least as well as existing approaches based on feedforward neural networks. It has also been demonstrated how this approach could be extended to real-valued problems, such as function approximation and time series prediction. This paper investigates the problem of choosing the best network for real-valued approximation problems. Firstly, the nature of the network parameters, how they are interrelated, and how they affect the performance of the system are clarified. Then we address the problem of choosing the best values of these parameters. We present two model selection tools in this regard, the first using a simple statistical model of the network, and the second using structural information about the network components. The resulting network selection methods are demonstrated and their performance tested on several benchmark and applied problems. The conclusions look at future research issues for further improving the performance of the clustering network.

This article considers a hybrid data backup model for a file system, which combines both conventional magnetic disk (MD) and write-once, read-many optical disk (OD). Since OD recently is a lower cost medium as well as a longer life medium than the ordinary MD, this kind of backup configuration is just recognized to be important. We mathematically formulate the hybrid data backup model and obtain the closed-form average cost rate when the system failure time and the recovery time follow exponential distributions. Numerical calculations are carried out to obtain the optimal backup policy, which is composed of two kinds of backup sizes from the main memory to MD and from MD to OD and minimizes the average cost rate. In numerical examples, the dependence of the optimal backup policy on the failure and the recovery mechanism is examined.

A design method of 2-D lattice digital filter using the Genetic Algorithm (GA) is proposed. By using the GA. 2-D all-pole lattice filter with the cascade connection of transversal (all-zoro) filter is designed directly from a given desired frequency responce.

Based on a simple model for the statistical error characteristics of range sensing, a numerical scheme called renormalization is presented for optimally fitting a planar surface to data points obtained by range sensing. The renormalization method has the advantage that not only an optimal fit is computed but also its reliability is automatically evaluated in the form of the covariance matrix. Its effectiveness is demonstrated by numerical simulation. A scheme for visualizing the reliability of computation by means of the primary deviation pair is also presented.

A new method is proposed for realizing a flexible change detection which is free from the limitation that multitemporal images must have the same spectral bands whose center wavelength and bandwidth are identical. As spaceborne multispectral scanners are continuously improved for performance and new scanners do not necessarily have the same spaectral bands for observation, this limitation is a serious obstacle for detecting long term temporal change. The proposed method removes this limitation by using an image normalization technique based on multiple regression analysis. The method is successfully applied to actual remotely sensed multitemporal images.