This paper presents a new sort of multilayer piezoelectric ceramic transformer for switching regulated power supplies. This piezoelectric transformer operates in the second thickness extensional vibration mode. Its resonant frequency is higher than 1 MHz. First, numerical simulation was implemented using a distributed constant electromechanical equivalent circuit method. It was calculated that this piezoelectric transformer, which has higher than 200 mechanical quality factor Qm, could work with higher than 90% efficiency and in more than 20-W/cm3 high power density. Second, a trially fabricated transformer, which is 15 mm long, 15 mm wide and 2.2 mm thick, was examined. Modified PbTiO3 family ceramics were used for the piezoelectric transformer material, because of the large anisotropy between electromechanical coupling factors kt and kp. Obtained results indicate that the piezoelectric transformer has good resonant characteristics, with little spurious vibration, and exhibits 16-W/cm3 power density with high efficiency at 2 MHz. Moreover, a switching regulated power supply, applying the piezoelectric ceramic transformer, was built and examined.

This paper presents a fast and practical routing algorithm implemented on a supercomputer. In previously reported work, routing has been accelerated by executing the maze algorithm on parallel processing elements. However, although many parallel algorithms and special architectures have been introduced, practical aspects have not been addressed. We therefore present a novel approach that uses a vector processor as a routing accelerator and a wavefront control algorithm in order to avoid the wasteful searches that often occur in industrial routing problems. Experimental results that show the performance of a supercomputer using these algorithms is equivalent to over 1800 VAXMIPS, the fastest yet reported for routing accelerators. Results with industrial data also prove the validity of our approach.

In this letter an SR-latch circuit using Hopfield neural networks is introduced. An energy function suited for a neural SR-latch circuit is defined for which the global convergence is guaranteed. We also demonstrate how to compose master-slave (M/S) SR- and JK-flip flops of novel SR-latch circuits, and further an asynchronous binary counter of M/S JK-flip flops. Computer simulations are included to illustrate how each presented circuit operates.

A queueing model suitable for multimedia packets with Poisson and batch Poisson arrivals is studied. In the queueing model, priority is given to the packets with batch Poisson arrival, and the packets with Poisson arrival, accumulated in a buffer, are routed by utilizing intervals of the packets with priority. The queueing performance of the proposed model is evaluated by the mean system delay. We also consider the effect of batch size and the ratio of the traffic with batch Poisson arrival and the one with Poisson arrival on the mean system delay. It is found that the proposed queueing model is useful to reduce the mean system delay of the packets with Poisson arrival, while maintaining the means system delay of the packets with batch Poisson arrival.

The warp model of the extended Hough transform (EHT) has been proposed to design the explicit expression of the transform function of EHT. The warp model is a skewed parameter space (R(µ,ξ), φ(µ,ξ)) of the space (µ,ξ), which is homeomorphic to the original (ρ,θ) parameter space. We note that the introduction of the skewness of the parameter space defines the angular and positional sensitivity characteristics required in the detection of lines from the pattern space. With the intent of contributing some solutions to basic computer vision problems, we present theoretically a dynamic and centralfine/peripheral-coarse camera vision architecture by means of this warp model of Hough transform. We call this camera vision architecture askant vision' from an analogy to the human askant glance. In this paper, an outline of the EHT is briefly shown by giving three functional conditions to ensure the homeomorphic relation between (µ,ξ) and (ρ,θ) parameter spaces. After an interpretation of the warp model is presented, a procedure to provide the transform function and a central-coarse/peripheralfine Hough transform function are introduced. Then in order to realize a dynamic control mechanism, it is proposed that shifting of the origin of the pattern space leads to sinusoidal modification of the Hough parameter space.

It is shown that a self–recurrent fuzzy inference can cause chaotic responses at least three membership functions, if the inference rules are set to represent nonlinear relations such as pie–kneading transformation. This system has single input and single output both with crisp values, in which membership functions is taken to be triangular. Extensions to infinite memberships are proposed, so as to reproduce the continuum case of one–dimensional logistic map f(x)=Ax(1–x). And bifurcation diagrams are calculated for number N of memberships of 3, 5, 9 and 17. It is found from bifurcation diagrams that different periodic states coexist at the same bifurcation parameter for N9. This indicates multistability necessarily accompanied with hysteresis effects. Therefore, it is concluded that the final states are not uniquely determined by fuzzy inferences with sufficiently large number of memberships.

This paper describes a new feature extraction model (Active Model) which is extended from the active contour model (Snakes). Active Model can be applied to various energy minimizing models since it integrates most of the energy terms ever proposed into one model and also provides the new terms for multiple images such as motion and stereo images. The computational order of energy minimization process is estimated in comparison with a dynamic programming method and a greedy algorithm, and it is shown that the energy minimization process in Active Model is faster than the others. Some experimental results are also shown.

Introducing a general statistical model of image noise, we present an optimal algorithm for computing 3-D motion from two views without involving numerical search: () the essential matrix is computed by a scheme called renormalization; () the decomposability condition is optimally imposed on it so that it exactly decomposes into motion parameters; () image feature points are optimally corrected so that they define their 3-D depths. Our scheme not only produces a statistically optimal solution but also evaluates the reliability of the computed motion parameters and reconstructed points in quantitative terms.

This paper proposes a methodology for fine evaluation of the uncertain behaviors of systems affected by any fluctuation of internal structures and internal parameters, by the use of a new concept on the fuzzy mapping. For a uniformly convex real Banach space X and Y, a fuzzy mapping G is introduced as the operator by which we can define a bounded closed compact fuzzy set G(x,y) for any (x,y)∈X×Y. An original system is represented by a completely continuous operator f defined on X, for instance, in a form xλ(f(x)) by a continuous operator λ: YX. The nondeterministic fluctuations induced into the original system are represented by a generalized form of the fuzzy mapping equation xGβ (x,f(x)) {ζX|µG(x,f(x))(ζ)β}, in order to give a fine evaluation of the solutions with respect to an arbitrarily–specified β–level. By establishing a useful fixed point theorem, the existence and evaluation problems of the "β–level-likely" solutions are discussed for this fuzzy mapping equaion. The theory developed here for the fluctuation problems is applied to the fine estimation of not only the uncertain behaviors of system–fluctuations but also the validity of system–models and -simulations with uncertain properties.

Synchronization has been one of the problems in M–ary spread spectrum communication systems. In this letter, we propose the frame synchronization method using the Hadamard matrix and a frame synchronization method of PCM communication systems. Moreover, we analyze the probabilities of keeping synchronous state and frame renewal rates, and we evaluate the relationship between these probabilities and the number of stages of counters.

We report on an experimental hysteresis in the Hopfield networks and examine the effect of the hysteresis on some important characteristics of the Hopfield networks. The detail mathematic description of the hysteresis phenomenon in the Hopfield networks is given. It suggests that the hysteresis results from fully–connected interconnection of the Hopfield networks and the hysteresis tends to makes the Hopfield networks difficult to reach the global minimum. This paper presents a T–Model network approach to overcoming the hysteresis phenomenon by employing a half–connected interconnection. As a result, there is no hysteresis phenomenon found in the T–Model networks. Theoretical analysis of the T–Model networks is also given. The hysteresis phenomenon in the Hopfield and the T–Model networks is illustrated through experiments and simulations. The experiments agree with the theoretical analysis very well.

A new polarization splitter at optical frequencies is proposed. The basic structure of the device is a tapered velocity coupler which is composed of a straight and a dimensionally tapered slab waveguide on a LiNbO3 substrate. The numerical results obtained with the finite difference method indicate that extinction ratios of polarization less than 2% for both TE and TM modes are possible of realization under moderate control voltages and that the splitting characteristics are stable over a wide range of frequencies.

In this paper, the power dissipation issue is considered in the gate sizing procedure. In order to observe the tradeoff among area, delar and power dissipation in a circuit, gate sizing algorithms which can minimize power under delay constraints or minimize area under power and delay constraints are formulated. Experiments are performed to investigate the properties of area–power–delay tradeoff in the gate sizing procedure.

In this paper we propose a formal linearization method which permits us to transform nonlinear systems into linear systems by means of the Chebyshev interpolation. Nonlinear systems are usually represented by nonlinear differential equations. We introduce a linearizing function that consists of a sequence of the Chebyshev polynomials. The nonlinear equations are approximated by the method of Chebyshev interpolation and linearized with respect to the linearizing function. The excellent characteristics of this method are as follows: high accuracy of the approximation, convenient design, simple operation, easy usage of computer, etc. The coefficients of the resulting linear system are obtained by recurrence formula. The paper also have error bounds of this linearization which show that the accuracy of the approximation by the linearization increases as the order of the Chebyshev polynomials increases. A nonlinear filter is synthesized as an application of this method. Numerical computer experiments show that the proposed method is able to linearize a given nonlinear system properly.

In this letter we propose an interpolation technique for low-quality fingerprint images for highly reliable feature extraction. To improve the feature extraction rate, we extract fingerprint features by referring to both the interpolated image obtained by using a directional Laplacian filter and the high-contrast image obtained by using histogram equalization. Experimental results show the applicability of our method.

As a result of examination based on a newly available data set of millimeter-wave rain attenuation measured in the UK, it is found that the ITU-R specific rain attenuation model tends to appreciably underestimate millimeter-wave rain attenuation at frequencies above about 60GHz for the UK rain climate. This tendency is very similar to that previously reported for the Japanese experimental data at frequencies up to 245GHz. Furthermore, an alternative specific rain attenuation model based on the Japanese experimental data is found to be in fairly good agreement with the experimental data in the UK at frequencies up to 137GHz.

A globally and quadratically convergent algorithm is presented for solving nonlinear resistive networks containing transistors modeled by the Gummel-Poon model or the Shichman-Hodges model. This algorithm is based on the Katzenelson algorithm that is globally convergent for a broad class of piecewise-linear resistive networks. An effective restart technique is introduced, by which the algorithm converges to the solutions of the nonlinear resistive networks quadratically. The quadratic convergence is proved and also verified by numerical examples.

This paper presents a novel and successful optimization algorithm for optimizing Multiple-valued Logic (MVL) functions based on Petri net theory. Mathematical properties and Petri net modeling tools to implement MVL systems are introduced. On the basis of these properties and modeling tools, the optimization algorithm can synthesize, analyze and minimize an arbitrary quaternary logic function of n-input variables. The analysis technique of optimization algorithm is a well-established concept from both theories of MVL and Petri nets, and this can be applied to specify and optimize any MVL Petri net system. In this paper, Petri nets of Galois field have been proposed in order to form a complete system, which can be used to realize and construct VLSI circuit of any MVL function. Based on the Petri nets of Galois field and the proposed algorithm, the quaternary minimum and maximum functions have been analyzed, minimized, and designed. These applications have demonstrated the usefulness of optimization algorithm. Based on Petri net theory, the analysis revealed important information about MVL Petri net modeled systems, where this information has been used to evaluate the modeled system and suggest improvements or changes. For evaluation, advantages of the proposed method over a conventional logic minimization method are presented. Also, we have observed that the MVL Petri nets have the following advantages: Designers can exhibit clearly, simply and systematically any complex MVL Petri net nodel, number of concurrent operations is increased, number of places and transitions that are needed to realize a MVL model is very small, and the interconnection problems can be greatly reduced.

Recognizable series is a model of a sequential machine. A recognizable series S is represented by a triple (λ,µ,γ), called a linear representation of S, where λ is a row vector of dimension n specifying the initial state, γ is a column vector of dimension n specifying the output at a state, and µ is a morphism from input words to nn matrices specifying the state transition. The output for an input word w is defined as λ(µw) γ, called the coefficient of w in S, and written as (S,w). We present an algorithm which constructs a reduced linear representation of an unknown recognizable series S, with coefficients in a commutative field, using coefficient queries and equivalence queries. The answer to a coefficient query, with a word w, is the coefficient (S, w) of w in S. When one asks an equivalence query with a linear representation (λ,µ,γ), if (λ,µ,γ) is a linear representation of S, yes is returned, and otherwise a word c such that λ (µc) γ(S, c) and the coefficient (S, c) are returned: Such a word c is called a counterexample for the query. For each execution step of the algorithm, the execution time consumed from the initial step to the current step is O(mN 4M), where N is the dimension of a reduced linear representation of S, M is the maximum time consumed by a single fundamental operation (addition, subtraction, multiplication or division), and m is the maximum length of counterexamples as answers to equivalence queries returned until that step.

This paper presents a novel and successful logic synthesis method for optimizing ternary logic functions of any given number of input variables. A new optimization algorithm to synthesize and minimize an arbitrary ternary logic function of n-input variables can always lead this function to optimal or very close to optimal solution, where [n (n1)/2]1 searches are necessary to achieve the optimal solution. Therefore, the complexity number of this algorithm has been greatly reduced from O(3n) into O(n2). The advantages of this synthesis and optimization algorithm are: (1) Very easy logic synthesis method. (2) Algorithm complexity is O(n2). (3) Optimal solution can be obtained in very short time. (4) The method can solve the interconnection problems (interconnection delay) of VLSI and ULSI processors, where very fast and parallel operations can be achieved. A transformation method between operational and polynomial domains of ternary logic functions of n-input variables is also discussed. This transformation method is very effective and simple. Design of the circuits of GF(3) operators, addition and multiplication mod-3, have been proposed, where these circuits are composed of Josephson junction devices. The simulation results of these circuits and examples show the following advantages: very good performances, very low power consumption, and ultra high speed switching operation.