The propagation characteristic of 670 nm laser light on the array of 10 µm diameter polystyrene micro-sphere was studied. For the linearly arranged array of micro-spheres from one to 12, the propagated light intensity was decreased from 700 mV to 45 mV. However, the propagated light intensity in the air was significantly decreased and it became 2 mV at 60 µm from the optical fiber light source. For the micro-sphere array on the curvilinear line, the light intensity at 12th micro-sphere became 35 mV. This fact means the light was propagated almost same as that on the linear line. Whereas it is expected that three dimensionally crossing optical wave-guide is possible to be fabricated by arranging the micro-spheres.

This paper deals with the fundamental problem of automatic assessment of appearance of seam puckers on suits, and suggests possibilities for practical usage. Presently, evaluations are done by inspectors who compare standard photographs of suits to test samples. In order to avoid human errors, however, a method of automatic evaluation is desired. We process the problem as pattern recognition. As a feature we use fractal dimensions. The fractal dimensions obtained from standard photographs are used as template patterns. To make it easier to calculate fractal dimensions, we plot a curve representing the appearance of seam puckers, from which fractal dimensions of the curve can be calculated. The seam puckers in gray-scale images are confused with the material's texture, so the seam puckers must be enhanced for a precise evaluation. By using the concept of variance, we select images with seam puckers and enhance only the images with seam puckers. This is the novel aspect of this work. Twenty suits are used for the evaluation experiment and we obtain a result almost the same to the evaluation gained by inspection. That is, the evaluation of 11 samples is the same as that gained by inspection, the results of 8 samples differ by 1 grade, and the evaluation of 1 sample has a 2-grade difference. The results are also compared to the evaluation of the system using the Daubechies wavelet feature. The result of comparison shows that the present method gives a better evaluation than the system using the Daubechies wavelet.

In many fields such as city administration and facilities management, there are an increasing number of requests for a Geographic Information System (GIS) that provides users with automated mapping functions. A mechanism which displays 3D views of an urban scene is particularly required because it would allow the construction of an intuitive and understandable environment for managing objects in the scene. In this paper, we present a new urban modeling system utilizing both image-based and geometry-based approaches. Our method is based on a new concept in which a wide urban area can be displayed with natural photo-realistic images, and each object drawn in the view can be identified by pointing to it. First, to generate natural urban views from any viewpoint, we employ an image-based rendering method, Image Walkthrough, and modify it to handle aerial images. This method can interpolate and generate natural views by assembling several source photographs. Next, to identify each object in the scene, we recover its shape using computer vision techniques (a geometry-based approach). The rough shape of each building is reconstructed from various aerial images, and then its drawn position on the generated view is also determined. This means that it becomes possible to identify each building from an urban view. We have combined both of these approaches yielding a new style of urban information management. The users of the system can enjoy an intuitive understanding of the area and easily identify their target, by generating natural views from any viewpoint and suitably reconstructing the shapes of objects. We have made a prototype system of this new concept of GIS, which have shown the validity of our method.

We present here a study on the propagation characteristics of two-dimensional periodic structures. The method of mode matching is employed to formulate the boundary-value problem in an exact fashion, and a perturbation analysis is carried out to explain the wave phenomena associated with photonic band gap structures. The dispersion curves of 2D periodic medium and 2D periodic impedance surface are investigated in detail.

A radiated immunity test method using fields in a three-dimensional Helmholtz-coil set is described. The incident field to equipment under test (EUT) is generated by an orthogonally structured three sets of Helmholtz coil. Using this structure, the resultant field can be generated with arbitrary amplitude and direction. Therefore, the three dimensional immunity characteristics of an EUT can be cleared. The resultant field is calculated numerically and it is established that the field distribution is uniform inside the three dimensional Helmholtz-coil set. This is also confirmed through comparison with measured results. As an example, the immunity test of a cathode ray tube (CRT) display is made and the immunity map of CRT is obtained without reseting placement of EUT. Such map makes us understand the physical meaning and weak points.

A new efficient two-dimensional warping algorithm is presented, in which sub-optimal warping is attained by iterating DP-based local optimization of warp on partially overlapping subplane sequence. From an experimental comparison with a conventional approximation algorithm based on beam search DP, relative superiority of the proposed algorithm is established.

We propose a model for fault tolerant 3D processor arrays using one-and-half track switches. Spare processors are laid on the two opposite surfaces of the 3D array. The fault compensation process is performed by shifting processors on a continuous straight line (called compensation path) from a faulty processor to a spare on the surfaces. It is not allowed that compensantion paths are in the near-miss relation each other. Then, switches with only 4 states are needed to preserve the 3D mesh topology after compensating for faults. We give an algorithm in a convenient form for reconfiguring by hardware the 3D mesh arrays with faults. The algorithm can reconfigure the 3D mesh arrays in polynomial time. By computer simulation, we show the survival rates and the reliabilities of arrays which express the efficiencies of reconfiguration according to the algorithm. The reliabilities are compared with those of the model using double tracks for which the near-miss relation among compensation paths is allowed, but whose hardware overhead is almost double of that of the proposed model using one-and-half track. Finally, we design a logical circuit for hardware realization of the algorithm. Using the circuit, we can construct such a built-in self-reconfigurable 3D mesh array that the reconfiguration is done very quickly without an aid of a host computer.

A procedure for quickly developing highly integrated multifunctional MMICs by using the three-dimensional masterslice MMIC technology has been developed. The structures and advanced features of this technology, such as miniature transmission lines, a broadside coupler, and miniature function block circuits, enable multifunctional MMICs to be quickly and easily developed. These unique features and basic concept of the masterslice technology are discussed and reviewed to examine the advantages of this technology. As an example of quick MMIC development, an amplifier, a mixer, and a down-converter are fabricated on a newly designed master array.

Using Hopfield-type neural network model, we present an algorithm for reconstructing 3D mesh processor arrays using single-track switches where spare processors are laid on the six surfaces of a 3D array and show its effectiveness in terms of reconstruction rate and computing time by computer simulation. Next, we show how the algorithm can be realized by a digital neural circuit. It consists of subcircuits for finding candidate compensation paths, deciding whether the neural system reaches a stable state and at the time the system energy is minimum, and subcircuits for neurons. The subcircuit for each neuron including the other subcircuits can only be made with 16 gates and two flip-flops. Since the state transitions are done in parallel, the circuit will be able to find a set of compensation paths for a fault pattern very quickly within a time less than 1 µs. Furthermore, the hardware implementation of the algorithm leads to making a self-reconfigurable system without the aid of a host computer.

Feature selection is an integral part of any pattern recognition system. Removal of redundant features improves the efficiency of a classifier as well as cut down the cost of future feature extraction. Recently neural network classifiers have become extremely popular compared to their counterparts from statistical theory. Some works on the use of artificial neural network as a feature selector have already been reported. In this work a simple feature selection algorithm has been proposed in which a fractal neural network, a modified version of multilayer perceptron, has been used as a feature selector. Experiments have been done with IRIS and SONAR data set by simulation. Results suggest that the algorithm with the fractal network architecture works well for removal of redundant informations as tested by classification rate. The fractal neural network takes lesser training time than the conventional multilayer perceptron for its lower connectivity while its performance is comparable to the multilayer perceptron. The ease of hardware implementation is also an attractive point in designing feature selector with fractal neural network.

We propose a new method to construct a four parameter family of quantum-mechanical point interactions in one dimension, which is known as all possible self-adjoint extensions of the symmetric operator T=-Δ C0(R \{0}). It is achieved in the small distance limit of equally spaced three neighboring Dirac's δ potentials. The strength for each δ is appropriately renormalized according to the distance and it diverges, in general, in the small distance limit. The validity of our method is ensured by numerical calculations. In general cases except for usual δ, the wave function discontinuity appears around the interaction and one can observe such a tendency even at a finite distance level.

Radio waves propagating through tunnels are strongly attenuated in the presence of discontinuities such as bends and branches. The useful structural modifications are requested to get better circumstances for radio waves in tunnels. In this paper, we propose several modifications arranged in a conventional T-junction of two-dimensional tunnels and analyze the transmission characteristics of radio waves by using the finite volume time domain (FVTD) method.

A new dynamic programming (DP) based algorithm for monotonic and continuous two-dimensional warping (2DW) is presented. This algorithm searches for the optimal pixel-to-pixel mapping between a pair of images subject to monotonicity and continuity constraints with by far less time complexity than the algorithm previously reported by the authors. This complexity reduction results from a refinement of the multi-stage decision process representing the 2DW problem. As an implementation technique, a polynomial order approximation algorithm incorporated with beam search is also presented. Theoretical and experimental comparisons show that the present approximation algorithm yields better performance than the previous approximation algorithm.

The conventional synthesis procedure of discrete time sparsely interconnected neural networks (DTSINNs) for associative memories may generate the cells with only self-feedback due to the sparsely interconnected structure. Although this problem is solved by increasing the number of interconnections, hardware implementation becomes very difficult. In this letter, we propose the DTSINN system which stores the 2-dimensional discrete Walsh transforms (DWTs) of memory patterns. As each element of DWT involves the information of whole sample data, our system can associate the desired memory patterns, which the conventional DTSINN fails to do.

The authors have proposed a design method for two-dimensional (2-D) separable-denominator (SD) periodically time-variant digital filters (PTV DFs) and confirmed their superiority over 2-D time-invariant DFs. In that result, the periodicity matrix representing the periodicity of the varying filter coefficients is, however, restricted to two cases. This paper extends that idea so that the input-output relation of 2-D SD PTV DFs with an arbitrary periodicity matrix can be determined. This enables us to design wide range of 2-D PTV DFs.

Image restoration using estimated parameters of image model and noise statistics is presented. The image is modeled as the output of a 2-D noncausal autoregressive (NCAR) model. The parameter estimation process is done by using the autocorrelation function and a biased term to a conventional least-squares (LS) method for the noncausal modeling. It is shown that the proposed method gives better results than the other parameter estimation methods which ignore the presence of the noise in the observation data. An appropriate image model selection process is also presented. A genetic algorithm (GA) for solving a multiobjective function with single constraint is discussed.

A novel approach was proposed to recognize the non-rigid 3D objects from their corresponding 2D images by combining the benefits of the principal component analysis and the geometric hashing. For all of the object models to be recognized, we calculated the statistical point features of the training shapes using principal component analysis. The results of the analysis were a vector of eigenvalues and a matrix of eigenvectors. We calculated invariants of the new shapes that undergone a similarity transformation. Then added these invariants and the label of the model to the model database. To recognize objects, we calculated the necessary invariants from an unknown image and used them as the indexing keys to retrieve any possible matches with the model features from the model database. We hypothesized the existence of an instance of the model in the scene if the model's features scored enough hits on the vote count. This approach allowed us to store the rigid and the non-rigid object models in a model database and utilized them to recognize an instance of model from an unknown image.

This paper discusses a design technique for multidimensional (M-D) multirate filters which cause no checkerboard distortion. In the first part of this paper, a necessary and sufficient condition for M-D multirate filters to be checkerboard-distortion-free is derived in the frequency domain. Then, in the second part, this result is applied to a scanning line conversion system for television signals. To confirm the effectiveness of the derived condition, band-limiting filters with and without considering the condition are designed, and the results by these filters are compared. A reducibility of the number of delay elements in such a system is also considered to derive efficient implementation.

The checkerboard effect is caused by the periodic time-variant property of multirate filters which consist of up-samplers and digital filters. Although the conditions for some one-dimensional (1D) multirate systems to avoid the checkerboard effect have been shown, the conditions for Multidimensional (MD) multirate systems have not been considered. In this paper, some theorems about the conditions for MD multirate filters without checkerboard effect are derived. In addition, we also consider MD multirate filter banks without checkerboard effect. Simulation examples show that the checkerboard effect can be avoided by using the proposed conditions.

Recently, a great deal of effort has been devoted to the design problem of "constrained least squares M-D FIR filter" because a significant improvement of the squared error is expected by a slight relaxation of the minimax error condition. Unfortunately, no design method has been reported, which has some theoretical guarantee of the convergence to the optimal solution. In this paper, we propose a class of novel design methods of "constrained least squares M-D FIR filter. " The most remarkable feature is that all of the proposed methods have theoretical guarantees of convergences to the unique optimal solution under any consistent set of prescribed maximal error conditions. The proposed methods are based on "convex projection techniques" that computes the metric projection onto the intersection of multiple closed convex sets in real Hilbert space. Moreover, some of the proposed methods can still be applied even for the problem with any inconsistent set of maximal error conditions. These lead to the unique optimal solution over the set of all filters that attain the least sum of squared distances to all constraint sets.