In this paper, symbols and numerals in topographic maps are recognized by the multi-angled parallelism (MAP) matching method, and small dots and lines are extracted by the MAP operation method. These results are then combined to determine the value, position, and attributes of elevation marks. Also, we reconstruct three dimensional surfaces described by contours, which is difficult even for humans since the elevation symbols are sparse. In reconstruction of the surface, we define an energy function that enfores three constraints: smoothness, fit, and contour. This energy function is minimized by solving a large linear system of simultaneous equations. We describe experiments on 25,000:1 scale topographic maps of the Tsukuba area.

It is demonstrated that the enhancement in the functional capability of an elemental transistor is quite essential in developing human-like intelligent electronic systems. For this purpose we have introduced the concept of four-terminal devices. Four-terminal devices have an additional dimension in the degree of freedom in controlling currents as compared to the three-terminal devices like bipolar and MOS transistors. The importance of the four-terminal device concept is demonstrated taking the neuron MOS transistor (abbreviated as neuMOS or νMOS) and its circuit applications as examples. We have found that any Boolean functin can be realized by a two-stage configuratin of νMOS inverters. In addition, the variable threshold nature of the device allows us to build real-time reconfigurable logic circuits (no floating gate charging effect is involved in varying the threshold). Based on the principle, we have developed Soft-Hardware Logic Circuits and Real-Time Rule-Variable Data Matching Circuits. A winner-take-all circuit which finds the largest signal by hardware parallel processing has been also developed. The circuit is applied to building an associative memory which is different from Hopfield network in both principle and operation. The hardware algorithm in which binary, multivalue, and analog operations are merged at a very device level is quite essential to establish intelligent information processing systems based on highly flexible, real-time programmable hardwares realized by four-terminal devices.

The demand for mobile communication services is rapidly increasing, because the mobile communication service is synonymy of an ideal communication style realizing communication in anytime, anywhere and with anyone. The development of economic and social activities is a primary factor of the increasing demand for mobile communication services. The demand stimulates the development of technology in mobile communication including personal communication services. Thus mobile communication has been one of the most active research in communications in the last several years. There exist various problems to which graph & network theory is applicable in mobile communication services (for example, channel assignment algorithm in cellular system, protocol in modile communication networks and traffic control in mobile communication ). A model of a cellular system has been formulated using a graph and it is known that the channel assignment problem is equivalent to the coloring problem of graph theory. Recently, two types of coloring problems on graphs or networks related to the channel assignment problem were proposed. Mainly, we introduce these coloring problems and show some results on these problems in this paper.

An integrator using UGB (unity-gain buffer) is proposed. The UGB has gain error. To improve the gain error of UGB in the integrator, a compensation technique of the gain error of UGB is proposed. Next, second-order ΣΔ A/D converter using UGB integrator with gain-error compensator is proposed. In the proposed circuit, the influence of input-output characteristic is simulated. In the simulation results, the improvement is confirmed. In addition, performance limiting factors due to non ideal effects, e.g., parasitic capacitance and offset voltage, are considered. Validity of the proposed compensation technique for each factor is confirmed in the simulation results.

Real-time collision detection is one of the most important intelligent processings in robotics. In collision detection, a large storage capasity is usually required to store the 3-dimensional information on the obstacles located in a workspace. Moreover, high-computational power is essential in not only coordinate transformation but also matching operation. In the proposed collision detection VLSI processor, the matching operation is drastically accelerated by using a content-addressable memory (CAM). A new obstacle representation based on a union of rectangular solids is also used to reduce the obstacle memory capacity, so that the collision detection can be performed by only magnitude comparison in parallel. Parallel architecture using several identical processor elements (PEs) is employed to perform the coordinate transformation at high speed, and each PE performs coordinate transformation at high speed based on the COordinate Rotation DIgital Computation (CORDIC) algorithms. When the 16 PEs and 144-kb CAM are used, the performance is evaluated to be 90 ms.

In this paper, we propose DSVMA (Data Steal into Voice Multiple Access) scheme for integration of voice and data in wireless information networks. By using speech activity detectors and effective downstream control signals, DSVMA enables data terminals to transmit multi-packet messages when voice terminals are in silent periods. The S-G (throughput versus offered load) performance of the DSVMA system and the blocking probabilities of both the second generation systems and the DSVMA systems are evaluated by the static analysis. A dynamic analysis of a system with finite number of terminals is also presented using an approximate Markov analysis method. Some numerical examples are given in the paper. As a result, it is shown that DSVMA can improve the channel utility efficiency of a circuit-switched TDMA (Time Division Multiple Access) wireless communication system and is directly applicable for second generation wireless information systems.

A method for extracting and recognizing character strings from unformed document images, which have inclined character strings and have no structure at all, is described. To process such kinds of unformed documents, previous schemes, which are intended only to deal with documents containing nothing but horizontal or vertical strings of characters, do not work well. Our method is based on the idea that the processes of recognition and extraction of character patterns should operate together, and on the characteristic that the character patterns are located close to each other when they belong to the same string. The method has been implemented and applied to several images. The experimental results show the robustness of our method.

This paper presents a new line extraction method to capture vectors based on contours and skeletons from line drawing raster images in which the lines are touched by characters or other lines. Conventionally, two line extraction methods have generally been used. One is a thinning method. The other is a medial line extraction method based on parallel pairs of contours. The thinning method tends to distort the extracted lines, especially at intersections and corners. On the other hand, the medial line extraction method has a poor capability as regards capturing correct lines at intersections. Contours are able to maintain edge shapes well, while skeletons preserve topological features; thus, a combination of these features effectively leads to the best fitting line. In the proposed method, the line which best fits the original image is selected from among various candidate lines. The candidates are created from several merged short skeleton fragments located between pairs of short contour fragments. The method is also extended to circular arc fitting. Experimental results show that the proposed line fitting method is effective.

The Institute for Posts and Telecommunications Policy (IPTP) held its first character recognition competition in 1992 to ascertain the present status of ongoing research in character recognition and to find promising algorithms for handwritten numerals. In this paper, we report and analyze the results of this competition. In the competition, we adopted 3-digit handwritten postal code images gathered from live mail as recognition objects. Prior to the competition, 2,500 samples (7,500 characters) were distributed to the participants as traning data. By using about 10,000 different samples (29,883 characters), we tested 13 recognition programs submitted by five universities and eight manufacturing companies. According to the four kinds of evaluation criteria: recognition accuracy, recognition speed, robustness against degradation, and theroretical originality, we selected the best three recognition algorithms as the Prize of Highest Excellence. Interestingly enough, the best three recognition algorithms showed considerable diversity in their methodologies and had very few commonly substituted or rejected patterns. We analyzed the causes for these commonly substituted or rejected patterns and, moreover, examined the human ability to discriminate between these patterns. Next, by considering the complementary characteristics of each recognition algorithm, we studied a multi-expert recognition strategy using the best three recognition algorithms. Three kinds of combination rules: voting on the first candidate rule, minimal sum of candidate order rule, and minimal sum of dissimilarities rule were examined, and the latter two rules decreased the substitution rate to one third of that obtained by one-expert in the competition. Furthermore, we proposed a candidate appearance likelihood method which utilizes the conditional probability of each of ten digits given the candidate combination obtained by each algorithm. From the experiments, this method achieved surprisingly low values of both substitution and rejection rates. By taking account of its learning ability, the candidate appearance likelihood method is considered one of the most promising multi-expert systems.

The ultimate minimum energy of switching mechanism for MOS integrated circuits have been studied. This report elucidates the evaluation methods for minimum switching energy of instantaneous discharged mechanism after charging one, namely, recycled energy of the MOS device. Two approaches are implemented to capture this concept. One is a switching energy by the time-dependent gate capacitance (TDGC) model ; the other one by results developed by transient device simulation, which was implemented using Finite Element Method (FEM). It is understood that the non-recycled minimum swhiching energies by both approaches show a good agreement. The recycled energies are then calculated at various sub-micron gate MOS/SOI devices and can be ultra-low power of the MOS integrated circuits, which may be possible to build recycled power circuitry for super energy-saving in the future new MOS LSI. From those results, (1) the TDGC is simultaneously verified by consistent match of the non-recycled minimum switching energies; (2) the recycled switching energy is found to be the ultimate lower bound of power for MOS device; (3) the recycled switching energy can be saved up to around 80% of that of current MOS LSI.

In robot vision system, enormously large computation power is required to perform three-dimensional (3-D) instrumentation and object recognition. However, many kinds of complex and irregular operations are required to make accurate 3-D instrumentation and object recognition in the conventional method for software implementation. In this paper, a VLSI-oriented Model-Based Robot Vision (MBRV) processor is proposed for high-speed and accurate 3-D instrumentation and object recognition. An input image is compared with two-dimensional (2-D) silhouette images which are generated from the 3-D object models by means of perspective projection. Because the MBRV algorithm always gives the candidates for the accurate 3-D instrumentation and object recognition result with simple and regular procedures, it is suitable for the implementation of the VLSI processor. Highly parallel architecture is employed in the VLSI processor to reduce the latency between the image acquisition and the output generation of the 3-D instrumentation and object recognition results. As a result, 3-D instrumentation and object recognition can be performed 10000 times faster than a 28.5 MIPS workstation.

The issue about document structure recognition and document understanding is today one of interesting subjects from a viewpoint of practical applications. The research objective is to extract the meaningful data from document images interpretatively and also classify them as the predefined item data automatically. In comparison with the traditional image-processing-based approaches, the knowledge-based approaches, which make use of various knowledge in order to interpret structural/constructive features of documents, have been currently investigated as more flexible and applicable methods. In this paper, we propose a totally integrated paradigm for understanding table-form documents from a viewpoint of the architectural framework.

A bounded complex (BC) digital transfer function realized with a II-cascade structure of Lossless Bounded Complex (LBC) two-pairs is known to have low magnitude sensitivity. In this letter, it is shown that the two-pairs parameters depend directly on some invariants of the transfer function corresponding to the transmission zeros of the structure. An analysis of the existence and the numbering of these invariants leads to a simplified automated LBC filter structure design avoiding the need for polynomial manipulations. These results are also easily applied for the real filtering case.

In intelligent integrated systems such as robotics for autonomous work, it is essential to respond to the change of the environment very quickly. Therefore, the development of special-purpose VLSI processors for intelligent integrated systems with small latency becomes an very important subject. In this paper, we present a scheduling algorithm for high-level synthesis. The input to the scheduler is a behavioral description which is viewed as a data flow graph (DFG). The scheduler minimizes the latency, which is the delay of the critical path in the DFG, and minimizes the number of functional units and buses by improving the utilization rates. By using an integer linear programming, the scheduler optimally assigns nodes and arcs in the DFG into steps.

A system for segmentation of document image and ordering text areas is described, and applied to complex printed page layouts of both Japanese and English. There is no need to make any assumptions about the shape of blocks, hence the segmentation technique can handle not only skewed images without skew-correction but also documents where columns are not rectangular. In this technique, based on the bottom-up strategy, the connected components are extracted from the reduced image, and classiferd according to their local information. The connected components calssified as characters are then merged into lines, and the lines are merged into areas. Extracted text areas are classified as body, caption, header or footer. A tree graph of the layout of the body texts is made, and the texts ordered by preorder traversal on the graph. We introduce the concept of an influence range of each node, a procedure for handling titles, thus obtaining good results on various documents. The total system is fast and compact.

The Shannon-Hartley theorem for channel capacity presupposes signal transmission over time-invariant Gaussian channels. In a mobile radio environment, communications channels have randomly time-variant characteristics. In this paper, an expression for the average capacity of Rician fading channels is derived. It is shown that the average capacity of Rician channels is always lower than that of the Gaussian channel, while the Rayleigh channel capacity values represent the worst situation. In addition, the Rician channel capacity is examined when reception by a maximal-ratio combining technique with M-branches is employed, indicating its positive effect on channel average capacity when weak signal power or severe fading conditions are present. Finally, the relation between Rician and Rayleigh fading environment with respect to channel average capacity is discussed.

Data of system parameters of real systems have some uncertainty and they should be given by sets (or intervals) rather than fixed values. To analyze and design systems contaning such uncertain parameters, it is required to represent and treat uncertainty in data of parameters, and to compute value sets of characteristic polynomials and transfer functions. Interval arithmetic is one of the most powerful tools to perform such subjects. In this paper, Polygon Interval Arithmetic (PIA) on the set of polygons in the complex plane is considered, and the data structure and algorithms to execute PIA efficiently is proposed. Moreover, practical examples are shown to demonstrate how PIA is useful to compute the evaluation of value sets.

This paper presents an analysis of the dose rate in tissue irradiated by an electromagnetic near field of a circular loop antenna. An analytical model comprised of a circular loop antenna located in the vicinity of the semi-infinite plane of a homogeneous biological medium was formulated. A quasi-static hypothesis was not introduced. The theoretical formulation was rigorously developed based on Maxwell equations which used an electric vector potential, cylindrical coordinates and a Hankel transform. The internal electric field E and the specific absorption rate (SAR) were adopted as indices for the dose in the tissue. This formulation was applied to the dosimetry of a high-frequency therapeutic device (HFTD) and experiment of irradiation to a frog web. The frequency of the applied electro-magnetic fields (EMF) was 9-10MHz. The distance between the antenna and tissue was 2.0-3.2mm. The dose of HFTD were 0.75V/m and 0.35mW/kg, respectively. The dose of experiment of the irradiation to a frog web were 0.42-2.08V/m and 0.11-2.69mW/kg, respectively. The SAR values obtained by this analysis were small enough to conclude that the effects were non-thermal. The calculated SARs of these experiments were compared with estimated SARs in experiments on calcium efflux change due to a weak modulated RF field. All were found to be of the same order of magnitude.

Pitch frequency is a basic characteristic of human voice, and pitch extraction is one of the most important studies for speech recognition. This paper describes a simple but effective technique to obtain correct pitch frequency from candidates (pitch candidates) extracted by the short-range autocorrelation function. The correction is performed by a neural network in consideration of the time coutinuation that is realized by referring to pitch candidates at previous frames. Since the neural network is trained by the back-propagation algorithm with training data, it adapts to any speaker and obtains good correction without sensitive adjustment and tuning. The pitch extraction was performed for 3 male and 3 female announcers, and the proposed method improves the percentage of correct pitch from 58.65% to 89.19%.

Transmission characteristics of CPW bends having various curvatures and a fixed bend angle were measured. It was found that the transmission level shows dips at some particular frequencies, and that the dips are less pronounced as the radius of curvature becomes larger.