We apply neural networks to implement a line shape recognition/classification system. The purpose of employing neural networks is to eliminate target-specific algorithms from the system and to simplify the system. The system needs only to be trained by samples. The shapes are captured by the following operations. Lines to be processed are segmented at inflection points. Each segment is extended from both ends of it in a certain percentage. The shape of each extended segment is captured as an approximate curvature. Curvature sequence is normalized by size in order to get a scale-invariant measure. Feeding this normalized curvature date to a neural network leads to position-, rotation-, and scale-invariant line shape recognition. According to our experiments, almost 100% recognition rates are achieved against 5% random modification and 50%-200% scaling. The experimental results show that our method is effective. In addition, since this method captures shape locally, partial lines (caused by overlapping etc.) can also be recognized.

Advanced Traveller Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) require real-time traffic data to observe and control the trafic flow. Still, there is a lack of proficient traffic monitoring systems. One method to collect such data is using particular equipped vehicles, called probes, transmitting experienced travel times to base stations which in turn are connected to a traffic control center. In this paper we analyse the performance of a radio network for collecting real-time traffic data from probes. The results reveal that random transmission of traffic reports is a (spectrum) efficient, inexpensive and flexible method for collecting road traffic data that can provide reliable traffic monitoring.

In this paper, authors discuss on a lexicon directed algorithm for recognition of unconstrained handwritten words (cursive, discrete, or mixed) such as those encountered in mail pieces. The procedure consists of binarization, presegmentation, intermediate feature extraction, segmentation recognition, and post-processing. The segmentation recognition and the post-processing are repeated for all lexicon words while the binarization to the intermediate feature extraction are applied once for an input word. This algorithm is essentially non hierarchical in character segmentation and recognition which are performed in a single segmentation recognition process. The result of performance evaluation using large handwritten address block database, and algorithm improvements are described and discussed to achieve higher recognition accuracy and speed. Experimental studies with about 3000 word images indicate that overall accuracy in the range of 91% to 98% depending on the size of the lexicon (assumed to contain correct word) are achievable with the processing speed of 20 to 30 word per minute on typical work station.

This paper proposes a new burst coherent demodulator that improves transmission quality of microcellular TDMA/TDD systems for personal communications and has configuration suitable for low power consumption with LSIC-implementation. To achieve the better transmission quality, the proposed demodulator employs coherent detection with a unique carrier recovery scheme that can operate without any preamble for carrier recovery. In addition, the demodulator uses a clock recovery scheme with clock phase estimation using twice differentiation, which eliminates hangup and attains fast clock acquisition at 2 samples/symbol. Experimental results clarify the superiority of the proposed coherent demodulator for microcellular TDMA/TDD systems. The proposed coherent demodulator reduces the irreducible frame error rate by 40%, and achieves 4dB improvement at the frame error rate of 10% compared with differential detection under the Rayleigh fading (fD/fs=810-5, τrms/Ts=510-2) typical of personal communication environments.

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.

The present study describes using the state transition type of drawing understanding framework to construct a multi-purpose drawing understanding system. This new system employs an understanding process that complies with the understanding rules, which are easily obtained by the user. The same set of user-provided rules must be used for the same type of target drawings, but for slightly different ones, fine tuning is required to obtain understanding rules. To overcome this inherent drawback in constructing drawing understanding systems, we extended the system using a newly constructed understanding rule generating support system. The resultant integrated system is based on a man-machine cooperation type interface, and can automatically generate rules from user-provided simple interactions using a graphical user interace (GUI). To obtain efficient rule generation, the system employs an inductive inference method as a learning algorithm. Map-drawing experiments were successfully carried out, and an evaluation based on a rule leaning error criterion subsequently revealed an efficient rule generation process.

This paper presents an algorithm for string searching in a character lattice. A character lattice, which is obtained through a character recognition process, is a general and flexible data structure that represents many hypothesized strings in a document image. In this paper, the authors propose a simple and efficient algorithm; it consists of a single loop of some set-operations and scans the character lattice only once. The authors also describe two actual implementations of the algorithm; one uses Bit-Arrays and the other a Trie. Owing to its bir parallelism, the Bit-Array approach is able to search for a single pattern faster than the Trie approach, and is easily extended to complex matchings such as an approximate one. It is suited for document retrieval systems that need to search for a keyword as fast as possible. A hashed compact version of the character lattice is also useful to increase the speed of the search for a single pattern. In contrast, the Trie approach is able to search for a large number of patterns simultaneously, and is suited for document understanding systems that need to extract words from the character lattice. The experimental results have shown that both approaches achieve high performance.

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.

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.

This paper discusses a digital neuroprocessor named Quantizer Neuron Chip (QNC) employing the Quantizer Neuron model and two newly developed schemes; "concurrent processing of quantizer neuron" and "removal of ineffective calculations". QNC simulates neural networks named the Multi-Functional Layered Network (MFLN) with 64 output neurons, 4672 quantizer neurons and two million synaptic weights and can be used for character or image recognition and learning. The processing speed of the chip achieved 1.6 µseconds per output neuron for recognition and 20 million connections updated per second (MCUPS) for learning. In addition, QNC can execute multichip operation for increasing the size of networks. We applied QNC to handwritten numeral recognition and realized high speed recognition and learning. QNC is implemented in a 1.2 µm double metal CMOS with sea of gates' technology and contains 27,000 gates on a 10.9910.93 mm2 chip.

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.

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.

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.

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.

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.

This paper examines a novel digital modulation/multiple access technique called Multi-Carrier Code Division Multiple Access (MC-CDMA) where each data symbol is transmitted at multiple narrowband subcarriers. Each subcarrier is encoded with a phase offset of 0 or π based on a spreading code. Analytical results are presented on the performance of this modulation scheme in an indoor wireless multipath radio channel.

In this letter, we compare the three compound methods of the Multiple-scale technique to improve the quality of the scale values estimated by the method of fuzzy categories. The results show that the maximum compound method brings higher ability to estimate the scale values than the other methods despite categories used in the scale.

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.

This paper gives field experimental results on 16-ary quadrature amplitude modulation/time division multiple access (16QAM/TDMA) and trellis coded 16QAM/TDMA systems for land mobile communications in order to evaluate its capability of achieving large capacity and high quality data transmission. Pilot symbol aided space diversity and symbol timing synchronization based on maximum likelihood (ML) estimation are applied to both 16QAM/TDMA and trellis coded 16QAM/TDMA to improve transmission quality. For the trellis coded 16QAM/TDMA, trellis coding with Viterbi decoding and 2-frame symbol interleaving are further employed. The field experiments were conducted in the Tokyo metropolitan area of Japan. The results show that 16QAM/TDMA and trellis coded 16QAM/TDMA are practical modulation/access schemes for land mobile communication systems.

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.