On mutually coupling lines, the transmission signal is dispersively propagated by crosstalk coupling between lines and shows complex propagation characteristics caused by reciprocal reflections. Usually, the differential equation and the integral equation have been applied to analyze the solutions of transmission lines. In this paper, we propose a different analytical method of the propagation characteristics of signal and crosstalk noise. By setting up crosstalk coupling line as a sectionally divided digital transmission network and by using the signal flow graph and the difference equation, the propagation characteristics in the frequency domain, the space domain and the time domain on mutually coupling lines can be obtained. To verify the validity of this method and analyze the complex propagation problems, we first study the crosstalk characteristics of a twisted pair cable via the third circuit by unidirectional coupling. Subsequently we will analyze the coupling theory of bidirectional coupling lines.

The effects of Gaussian electromagnetic noise and non-Gaussian one on TV picture degradation are studied by using a composite noise generator which can control noise parameters. Three kinds of still pictures and four kinds of motion pictures are tested, and the picture degradation is subjectively evaluated with five-grade impairment scale. The tendency of the picture degradation against the every picture is almost the same. But MOS (Mean Opinion Score) between still picture and motion picture degradation is different in some measure when the power of burst noise is small.

The potential attenuation process of charged human body (HB) is analyzed. A two-dimensional circuit model is presented for predicting the potential attenuation characteristics of the HB charged on the floor. The theoretical equation for the HB potential is derived in the closed form in the Laplacian transformation domain, and the numerical inverse Laplace transform is used to compute it. The half-life or relaxation time of the HB potential for decay is numerically examined with respect to the electrical parameters of shoes. The experiment is also conducted for verifying the validity of the computed result.

This paper proposes a new approach for the development of a module generator that can parameterize both the size and the structure of layout. The proposed method acquires a design procedure from the design process of a designer, and reuses it to synthesize new layouts with different input parameters that affect the size or the structure of layout. In this method, a designer creates a module layout on a layout editor instead of writing a program. From his design process, a procedure to synthesize the layout is automatically derived. Then, it is generalized so that it could be valid under different values of input parameters. The generalized procedure is independent of design rules, and is capable of synthesizing error-free module layouts of different size and structure. Also, the procedure includes designer's requirements on how the layout should be designed. The experimental results of applying the approach for developing generators of analog device components show effectiveness of our approach.

We propose a new compaction problem that allows layout elements to have many shape possibilities. The objective of the problem is to find not only positions but also shapes of layout elements. We present an efficient method to solve the problem--compaction with shape optimization. This method simplifies the problem by considering the optimization of shapes only for the layout elements on a critical path. The layout is compacted step by step while optimizing the shapes of layout elements. Another importance of this compaction technique is that it makes layout to be "recyclable" for other set of device parameters. The experimental examples, which attempt shape optimization and recycle of analog layout, confirms the importance and efficiency of our method.

A systematic theory of the optimum multi-path interpolation using parallel filter banks is presented with respect to a family of n-dimensional signals which are not necessarily band-limited. In the first phase, we present the optimum spacelimited interpolation functions minimizing simultaneously the wide variety of measures of error defined independently in each separate range in the space variable domain, such as 8 8 pixels, for example. Although the quantization of the decimated sample values in each path is contained in this discussion, the resultant interpolation functions possess the optimum property stated above. In the second phase, we will consider the optimum approximation such that no restriction is imposed on the supports of interpolation functions. The Fourier transforms of the interpolation functions can be obtained as the solutions of the finite number of linear equations. For a family of signals not being band-limited, in general, this approximation satisfies beautiful orthogonal relation and minimizes various measures of error simultaneously including many types of measures of error defined in the frequency domain. These results can be extended to the discrete signal processing. In this case, when the rate of the decimation is in the state of critical-sampling or over-sampling and the analysis filters satisfy the condition of paraunitary, the results in the first phase are classified as follows: (1) If the supports of the interpolation functions are narrow and the approximation error necessarily exists, the presented interpolation functions realize the optimum approximation in the first phase. (2) If these supports become wide, in due course, the presented approximation satisfies perfect reconstruction at the given discrete points and realizes the optimum approximation given in the first phase at the intermediate points of the initial discrete points. (3) If the supports become wider, the statements in (2) are still valid but the measure of the approximation error in the first phase at the intermediate points becomes smaller. (4) Finally, those interpolation functions approach to the results in the second phase without destroying the property of perfect reconstruction at the initial discrete points.

For symmetric cryptosystems, their transformations should have nonlinear elements to be secure against various attacks. Several nonlinearity criteria have been defined and their properties have been made clear. This paper focuses on, among these criteria, the propagation criterion (PC) and the strict avalanche criterion (SAC), and makes a further investigation of them. It discusses the sets of Boolean functions satisflying the PC of higher degrees, the sets of those satisfying the SAC of higher orders and their relationships. We give a necessary and sufficient condition for an n-input Boolean function to satisfy the PC with respect to a set of all but one or two elements in {0,1}n{(0,...,0)}. From this condition, it follows that, for every even n 2, an n-input Boolean function satisfies the PC of degree n 1 if and only if it satisfies the PC of degree n. We also show a method that constructs, for any odd n 3, n-input Boolean functions that satisfy the PC with respect to a set of all but one elements in {0,1}n{(0,...,0)}. This method is a generalized version of a previous one. Concerned with the SAC of higher orders, it is shown that the previously proved upper bound of the nonlinear order of Boolean functions satisfying the criterion is tight. The relationships are discussed between the set of n-input Boolean functions satisfying the PC and the sets of those satisfying the SAC.

This paper describes the method of applying the integral form of Maxwell's equations to the transmission-line network used in the spatial network method for the modeling of curved conductor surfaces. The techniques of dealing with the transmission-line network near cylindrical conductor surface are explained in detail. To compare exact solutions with computed values, a cylindrical cavity resonator is analysed. The resonant frequencies and unloaded Q's for the computed three modes are obtained with the error of about 1%. Moreover, applying this treatment to the waveguide with magnetron anodeshape cross section, a cutoff-constant is computed successfully. It is found that the treatment proposed in this paper can be used as the method for modeling of curved conductor surface in the spatial network method. It is also considered that this treatment can be extend to TLM method.

Dynamic Term Rewriting Calculus (DTRC) is a new computation model aiming at formal description and verification of algorithms treating Term Rewriting Systems (TRSs). In this paper, we show that we can use DTRC to mechanize explicit induction for proving an inductive theorem, that is, we can translate the statements of base and induction steps for proving by induction into a DTRC term. The translation reduces the proof of the statements into the evaluation of the corresponding DTRC term.

We define a new framework for rewriting graphs, called a formal graph system (FGS), which is a logic program having hypergraphs instead of terms in first-order logic. We first prove that a class of graphs is generated by a hyperedge replacement grammar if and only if it is defined by an FGS of a special form called a regular FGS. In the same way as logic programs, we can define a refutation tree for an FGS. The classes of TTSP graphs and outerplanar graphs are definable by regular FGSs. Then, we consider the problem of constructing a refutation tree of a graph for these FGSs. For the FGS defining TTSP graphs, we present a refutation tree algorithm of O(log2nlogm) time with O(nm) processors on an EREW PRAM. For the FGS defining outerplanar graphs, we show that the refutation tree problem can be solved in O(log2n) time with O(nm) processors on an EREW PRAM. Here, n and m are the numbers of vertices and edges of an input graph, respectively.

GaAs-based micromachining is a very attractive technique for integrating mechanical structures and active optical devices, such as laser diodes and photodiodes. For monolithically integrating mechanical parts onto laser diode wafers, the micromachining technique must be compatible with the laser diode fabrication process. Our micromachining technique features three major processes: epitaxitial growth (MOVPE) for both the structural and sacrificial layers, reactive dry-etching by chlorine for high-aspect, three-dimensional structures, and selective wet-etching by peroxide/ammonium hydroxide solution to release the moving parts. These processes are compatible with laser fabrication, so a cantilever beam structure can be fabricated at the same time as a laser diode structure. Furthermore, a single-crystal epitaxial layer has little residual stress, so precise microstructures can be obtained without significant deformation. We fabricated a microbeam resonator sensor composed of two laser diodes, a photodiode, and a micro-cantilever beam with an area of 400700 µm. The cantilever beam is 3 µm wide, 5 µm high, and either 110µm long for a 200-kHz resonant frequency or 50 µm long for a 1-MHz resonant frequency. The cantilever beam is excited by an intensity-modulated laser beam from an integrated excitation laser diode; the vibration signal is detected by a coupled cavity laser diode and a photodiode.

Long-wavelength 1.3 µm GaInAsP/InP vertical cavity surface-emitting lasers (VCSELs) have been demonstrated in an array configuration. With the strong current confinement by a buried heterostructure and the efficient optical feedback by a dielectric cavity, five VCSEL elements in a 24 array operated at room temperature with 5 mW total power output and wavelength error within 5%. The stacked planar optics including the VCSEL array is a promising optical transmitter in ultra large scale parallel optical communication systems.

A 3-dimensional specific thickness profile was fabricated on a thin glass diaphragm lens to reduce aberration at short focal distances for greater dynamic focusing. The deformation of the diaphragm was calculated by stress analysis utilizing the Finite Element Method (FEM). Geometric non linearity is considered in the FEM analysis. The glass diaphragm is 10 mm in diameter and the average thickness is 11 µm. To obtain both a curved shape and an optical surface on the glass diaphragm, the 3-dimensional precision grinding technique was utilized. The processed shape matches the designed one with less than 0.3 µm deviation, and the average surface roughness is 0.005 µm. Optical characteristics of the dynamic focusing lens having a specific thickness profile, were measured by Modulation Transfer Function (MTF) measurement equipment. At a focal distance of 250 mm, the specific thickness diaphragm lens resolution is 10 cycles/mm, whereas, the uniform thickness diaphragm is 4 cycles/mm. Even at other focal distances, the specific thickness diaphragm shows superior optical characteristics in comparison with those of the uniform thickness diaphragm. The 3-dimensional profile diaphragm resolution is 2.5 times finer at a focal distance of 250 mm, thus, being capable of displacement control for variable optic devices. This was achieved by employing semiconductor processing methods in conjunction with precision grinding techniques which are necessary for fabricating micro structures.

The efficiency of a guided-probe fault location process is affected by the number of the probed lines. This number depends on the size of the target area and the method by which a line is selected for probing. This paper presents a method for reducing the size of the target area in a sequential circuit by introducing the concepts of Type- and Type- faults. This paper also presents a method of selecting lines for probing in a more efficient way. The efficiency of the proposed methods is demonstrated by experimental results.

In the present paper, we attempt to show that the information about input patterns must be as small as possible for improving the generalization performance under the condition that the network can produce targets with appropriate accuracy. The information is defined with respect to the hidden unit activity and we suppose that the hidden unit has a crucial role to store the information content about input patterns. The information is defined by the difference between uncertainty of the hidden unit at the initial stage of the learning and the uncertainty of the hidden unit at the final stage of the learning. After having formulated an update rule for the information minimization, we applied the method to a problem of language acquisition: the inference of the past tense forms of regular and irregular verbs. Experimental results confirmed that by our method, the information was significantly decreased and the generalization performance was greatly improved.

The objective of this study is to realize a manipulator of 0.5 mm in outside diameter as a part of 'research and development of micro machine technology.' This manipulator is intended as a part of a working robot to fix or observe the inside wall of a small pipe. One of the important problems of this research is to establish a processing method of a tubular small structure. MIM, metal injection molding, has been adopted to fabricate such a small structure. As a processing method to machine small molds for MIM, finish processing with surface roughness of Rmax 0.1 µm has been under our research applying 'vibrational processing technology,' which was developed on our own. This paper presents the results of 'vibrational processing technology' surface finishing of molds for metal injection.

This paper describes an advanced rule-embedded neural network (RENN+) that has an extended framework for achieving a very tight integration of learning-based neural networks and rule-bases of existing if-then rules. The RENN+ is effective in pattern recognition with ill-posed conditions. It is basically composed of several component RENNs and an output RENN, which are three-layer back-propagation (BP) networks except for the input layer. Each RENN can be pre-organized by embedding the if-then rules through translation of the rules into logic functions in a disjunctive normal form, and can be trainded to acquire adaptive rules as required. A weight-modification-reduced learning algorithm (WMR) capable of standard regularization is used for the post-training to suppress excessive modification of the weights for the embedded rules. To estimate the effectiveness of the proposed RENN+, it was used for pattern recognition in a radar system for detection of buried pipes. This trial showed that a RENN+ with two component RENNs had good recognition capability, whereas a conventional BP network was ineffective.

A conventional anode coupled plasma etching process has been developed to etch 300 µm-deep cavities and 600 µm-through holes with nearly vertical sidewalls into single crystal silicon. An optimized SF6/O2 gas mixture results in a nearly vertical etching profile. A silicon wafer was fabricated with a large number of cavities and through holes with less than 1 percent uniformity. It was also experimentally confirmed that this process can be used to etch vertical cavities and through holes in single-crystal silicon with any orientation. This process has the advantage of unlimited etching depth and etching patterns. Advantages in mechanical strength are obtained because a micro-curve is formed at the bottom edge of the cavities. This etching process developed on a conventional plasma etching system was utilized to fabricate a torsional vibrator that consists of single-crystal silicon and Pyrex glass.

For estimating the radiated emission from a metallic enclosure, the authors have developed a numerical computational method which applied inverse analysis. A metallic enclosure containing a loop antenna was set up to be a model source for the numerical analysis. Magnetic fields around the enclosure were measured by measurement systems fabricated in the authors' laboratory. Using the measured magnetic fields, current distributions on the enclosure surface were determined by means of an inverse analysis utilizing the least squares method. From this surface current distribution, the electromagnetic field distributions were estimated by forward analysis on a cylindrical surface 3.0m in radius. The amount of the error in the estimated fields distribution was also discussed.

It is shown by the derivation of solution methods for an elementary optimization problem that the stochastic relaxation in image analysis, the Potts neural networks for combinatorial optimization and interior point methods for nonlinear programming have common formulation of their dynamics. This unification of these algorithms leads us to possibility for real time solution of these problems with common analog electronic circuits.