A capacitor-error-free SC voltage inverter with zero sensitivity to element-value variations is proposed. By virtue of the capacitor-error-free property, this SC voltage inverter is free from the capacitor mismatch. The performance of this SC voltage inverter has been confirmed from both the simulation and experiment.

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.

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.

This paper presents an overview of the SDC-I (Super Database Computer I) developed at the University of Tokyo, Japan. The purpose of the project was to build a high performance SQL server which emphasizes query processing over transaction processing. Recently relational database systems tend to be used for heavy decision support queries, which include many join, aggregation, and order-by operations. At present high-end mainframes are used for these applications requiring several hours in some cases. While the system architecture for high traffic transaction processing systems is well established, that for adhoc query processing has not yet adequately understood. SDC-I proved that a parallel machine could attain significant performance improvements over a coventional sequential machine through the exploitation of the high degree of parallelism present in relational query processing. A unique bucket spreading parallel hash join algorithm is employed in SDC, which makes the system very robust in the presense of data skew and allows SDC to attain almost linear performance scalability. SDC adopts a hybrid parallel architecture, where globally it is a shared nothing architecture, that is, modules are connected through the multistage network, but each module itself is a symmetric multiprocessor system. Although most of the hardware elements use commodity microprocessors for improved performance to cost, only the interconnection network incorporates the special function to support our parallel relational algorithm. Data movement over the memory and the network, rather than computation, is heavy for I/O intensive database processing. A dedicated software system was carefully designed for efficient data movement. The implemented prototype consists of two modules. Its hardware and software organization is described. The performance monitoring tool was developed to visualize the system activities, which showed that SDC-I works very efficiently.

In this paper, radio propagation in the medium-scale building is investigated at 2.5GHz band. In order to predict the propagation loss in any place, four major modes of propagation are considered: low-loss in line-of-sight (LOS) wave, corridor guided wave, direct transmission wave through obstructions, and the reentered wave. Based on the measured results of attenuation characteristics, the macroscopic parameters for the above mentioned modes of wave propagation are determined. Using these parameters, signal strengths are predicted with average standard deviation of 4.5dB. The fading characteristics are studied by measuring the Rician parameter and the correlation coefficient for 2-branch diversity antennas separated by 50cm. The Rician parameters are 2 in case of the LOS propagation, and 1 in case of the no LOS propagation. The two branch correlation coefficients are less than 0.5 within coverage of 80-95% in almost all the locations.

A new frequency hopped spread spectrum system is introduced. The frequency hopped signal is a combination of multi frequency and multi phase signals and is referred to as Frequency Hopped/Joint Frequency-Phase Modulation (FH/JFPM). A noncoherent receiver for the FH/JFPM signals is introduced and an exact expression for the bit error rate is obtained. A performance analysis of this system is given in the presence of broadband and partial-band noise jamming. The optimal jamming strategy is evaluated. The results show that under these jamming conditions the FH/JFPM perform better than the FH/M-ary DPSK and FH/M-ary FSK systems. It is also shown that for a given channel bandwidth and data rate, the FH/JFPM system has more processing gain than its FSK or DPSK counterparts.

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.

An integrated pen interface system was developed to allow effective Japanese text entry. It consists of sub-systems for handwriting recognition, contextual post-processing, and enhanced Kana-to-Kanji conversion. The recognition sub-system uses a hybrid algorithm consisting of a pattern matcher and a neural network discriminator. Special care was taken to improve the recognition of non-Kanji and simple Kanji characters frequently used in fast data entry. The post-processor predicts consecutive characters on the basis of bigrams modified by the addition of parts of speech and substitution of macro characters for Kanji characters. A Kana-to Kanji conversion method designed for ease of use with a pen interface has also been integrated into the system. In an experiment in which 2,900 samples of Kanji and non-Kanji characters were obtained from 20 subjects, it was observed that the original recognition accuracy of 83.7% (the result obtained by using the pattern matching recognizer) was improved to 90.7% by adding the neural network discriminator, and that it was further improved to 94.4% by adding the post-processor. The improved recognition accuracy for non-Kanji characters was particularly marked.

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.

This paper shows that when a pattern matching method used in optical character readers is highly accurate, it can be used effectively in on-line Japanese character recognition. Stroke matching methods used in previous conventional on-line character recognition have restricted the number and the order of strokes. On the other hand, orientation-feature pattern matching methods avoid these restrictions. The authors have improved a pattern matching method with the development in the flexible pattern matching (FPM) method, based on nonlinear shape normalization and nonlinear pattern matching, which includes the normalization-cooperative feature extraction (NCFE) method. These improvements have increased the recognition rate from 81.9% to 95.9%, when applied to the off-line database ETL-9 from the Electrotechnical Laboratory, Japan. When applied on-line to the examination of 151,533 Kanji and Hiragana characters in 3,036 categories, the recognition rate achieved 94.0%, while the cumulative recognition rate within the best ten candidates was 99.1%.

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.

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 feedback pattern recognition method using an inverse recall neural network model is proposed. The feedback method can adjust processing parameter values adaptively to individual patterns so as to produce reliable recognition results. In order to apply an adaptive control technique to such pattern recognition processings, the evaluation value for recognition uncertainty is determined to be a function with regard to an input pattern and processing parameters. In its feedback phase, the input pattern is fixed and processing parameters are adjusted to decrease the recognition uncertainty. The proposed neural network model implements two functions in this feedback recognition method. One is a discrimination as a kind of multi-layer feedforward model. The other is to generate an input modification so as to decrease the recognition uncertainty. The modification values indicate parts which are important for more certain recognition but are missed in the original input to the nerwork. The proposed feedback method can adjust prcessing parameter values in order to detect the important parts shown by the inverse recall network model. As explained in this paper, feature extraction parameter values are adaptively adjusted by this feedback method. After the inverse recall model and the feedback function are implemented, features are extracted again by using the modified feature extraction parameter values. The feature is classified by the feedforward function of the network model. The feedforward and feedback processings are repeated until a certain recognition result is obtained. This method was examined for hadwritten alpha-numerics with rotation distortion. The feedback method was found to decrease the rejection ratio at the same substitution error ratio with high efficiency.

We propose a new structure of antenna system to enhance the horizontal plane gain and control the antenna pattern, using passive loading. Our proposed structure can be applied to various kinds of antennas on a handset. We discuss the case of a λ/4 monopole antenna on a handset in this paper. In a new structure of λ/4 monopole antenna system, we show that, 1) the increase of the average gain about 5dB in the horizontal plane can be realized by an optimum load, 2) the antenna pattern can be controlled by changing the value of the passive load so as to have some desirable shapes, and 3) the antenna size can be made smaller by about 6% than the one with no loading because the optimum loading makes the resonant frequency lower. These results were confirmed by the calculations using the method of moments for the EFIE and the measurements.

Stored channel simulation for mobile radio channel can be the common base of the development of future world wide personal radio communication systems, especially for high bit-rate digital system. This paper proposes a mobile radio channel database which is suitable for the laboratory channel simulation using a simple stored channel simulator, also proposed by the author. The database enables the establishment of a mobile radio channel database containing worldwide channel data in a few discs of compact disc.

An automatic zip code recognition system for Japanese mail is proposed in this paper. It is assumed that a zip code is composed of three numerals and requited to be written in a specified frame. In actual images, however, the three numerals sometimes extend outside the specified frame and are not clearly separated. Considering this situation, the authors devised a system with two stages, the segmentation stage and the recognition stage. The segmentation stage consists of five steps: setting and adjusting of initial areas for numeral images (figures), calculation of the center of gravity of each figure, search for the horizontal and vertical boundaries of each figure, determination of the final area for each figure, and normalization of the figure in each final area. In the recognition stage, the Localized Arc Pattern Method (Arc method) proposed by Yoshimura et al. (1991) is implemented hierarchically; that is, a simple Arc method is applied first to each figure and a more complex one is applied subsequently unless the figure is identified in the first step. In the recognition process, every figure is judged as a numeral or otherwise rejected. The proposed system was applied to a database provided by the Institute for Post and Telecommunications Policy (IPTP). The segmentation algorithm yielded an adequate result. The recognition algorithm yielded scores as high as 90.6% in correct recognition rate and 0.7% in error rate. The best score of the precision index (P-index) specified by the IPTP was as low as 15.7 for the above mentioned IPTP database, while the score for another IPTP database was 16.9.

Finite state translation systems (fsts') are a widely studied computational model in the area of tree automata theory. In this paper, the string generating capacities of fsts' and their subclasses are studied. First, it is shown that the class of string languages generated by deterministic fsts' equals to that of parallel multiple context-free grammars, which are an extension of context-free grammars. As a corollary, it can be concluded that the recognition problem for a deterministic fsts is solvable in O(ne1)-time, where n is the length of an input word and e is a constant called the degree of the deterministic fsts'. In contrast to the latter fact, it is also shown that nondeterministic monadic fsts' with state-bound 2 can generate an NP-complete language.

This paper presents a mathematical formulation of a data path allocation and floorplanning problem using the mixed integer linear programming, and shows some experimental results. We assume that a data flow graph and the scheduled result are given in advance. The chip area and total wire length are used for the quality measures of the solution for the problem. This method is applied to some examples, and compared with the other method reported previously in the points of the solution and computation time.

A new efficient waveform relaxation technique based on dynamically overlapped partitioning scheme is presented. This overlapped partitioning method enables the application of waveform relaxation technique to bipolar VLSI circuits. Instead of fixed overlapping, we select the depth of overlapping dynamically based on the sensitivity criteria. By minimizing the overlapped area, we could reduce the additional computational overhead which results from overlapping the partitions. This overlapped waveform relaxation method has better convergence properties due to smaller error introduced at each step compared with standard relaxation techniques. When overlapped partitioning is used in the case of digital circuits, the waveforms obtained after first iteration are nearly accurate. Therefore, by using these waveforms as initial guess waveforms for the second iterations we can reduce Newton-Raphson iterations at each time point.

We propose a beam tracing frame which shifts together with either the guiding structure or the beam propagation in optical circuits. This frame is adaptive to the beam propagation analysis based on the finite-element method and can reduce the computational window size.