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 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.

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.

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.

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.

Distributed algorithms that entail successive rounds of message exchange are called decentralized consensus protocols. Several consensus protocols use a finite projective plane as a communication structure and require 4nn messages in two rounds, where n is the number of nodes. This paper presents an efficient communication structure that uses a finite projective plane with a duality of indices. The communication structure requires 2nn messages in two rounds, and can therefore halve the number of messages. It is shown that a finite projective plane with a duality can be constructed from a difference set, and that the presented communication structure has two kinds of symmetry.

Physical optics (PO) is an approximation method for high-frequency scattering and diffraction problems. But PO fields are inaccurate in the shadow region where the source is screened by the scatterer. It has been difficult to extract the mechanism of this error because PO includes numerical integration. In 2-D problems, PO fields are analytically and accurately expressed in terms of PO equivalent edge currents (PO-EECs) which represent the leading contributions of PO original integration. Comparison of PO in this form and geometrical theory of diffraction (GTD) which gives accurate fields in the shadow region, clarifies the cause of PO errors. For a scatterer with a corner, PO errors are mainly due to the rays emanating from the invisible edges. For a curved surface scatterer, the contributions penetrating the scatterer are small and main PO errors generally consist in PO-EECs itself.

In 1985, Kues et al. (Bioelectromagnetics, 6, pp.177-188, 1985) reported that corneal endothelial abnormalities were observed after a 4-hour exposure of anesthetized monkey eyes to 2.45GHz CW. We have traced their experimental study without anesthetization. Although we irradiated with power density exceeding the threshold of 30mW/cm2 obtained by them, we could not observe the same abnormalities as they did.

To study the biological effects of the ion-current commonly found under ultra-high voltage DC transmission lines, a technique was developed to evaluate the human exposure to the ion-current field. This technique is based on numerical analysis using the boundary element method. The difficulty of handling the space charge in the calculation was overcome by assuming a lumped source ion-current. This technique is applicable to a three-dimensionally complex object such as a human body. In comparison with theoretical values, the accuracy of this technique was evaluated to be satisfactory for our purposes. It was then applied to a human body in an ion-current field. The distribution of the electric field along the body surface was obtained. The general characteristics of the field distribution were essentially the same as in those without space charges. However, it was found that the strength of the field concentration was significantly enhanced by the space charges. Further, the field exposure when a human body was charged by an ion-current was evaluated. As the charged voltage increases, the position of the field concentration moves from a human's head toward his legs. But the shock of micro spark increases. This technique provides a useful tool for the study of biological effects and safety standards of ion-current fields.

This paper surveys the researches on biological and electeromagnetic environments in RF (radio frequency) and microwave regions in Japan. Publicized research reports on biological objectives, evaluation of exposure rate, electromagnetic environments and guideline for the protection from radio wave nuisances are briefly introduced. Some researches on the evaluation of the exposure rate caused by the near field effect of portable radio transceiver are reviewed. Radio frequency exposer protection guidelines in Japan are also described.

An improvement of Q evaluation is discussed. The Resonance Curve Area method was confirmed to give a deviation in the order of 6104. The result was three times more accurate than the widely known Q evaluating method which utilizes the cursor function installed in a network analyzer. A discussion is also made on the physical validity of the RCA method. It is shown that the application of the RCA method improves the accuracy of the cavity perturbation method. Actual measurements have shown that the deviation of dielectric constant is less than 1% and that of the loss tangent is less than 3%, in the order of 104. The accuracy of the RCA method was estimated to be three times that of the conventional cavity perturbation technique. The consistency of the perturbation with other methods has also confirmed. The accuracy comparison to more accurate formulae derived from a rigorous solution have shown that the difference is sufficiently small.

Artificial Neural Networks (ANN's) that are able to learn exhibit many interesting features making them suitable to be applied in several fields such as pattern recognition, computer vision and so forth. Learning a given input-output mapping can be regarded as a problem of approximating a multivariate function. In this paper we will report a theoretical framework for approximation, based on the well known sequences of functions named approximate identities. In particular, it is proven that such sequences are able to approximate a generally continuous function to any degree of accuracy. On the basis of these theoretical results, it is shown that the proposed approximation scheme maps into a class of networks which can efficiently be implemented with analog MOS VLSI or BJT integrated circuits. To prove the validity of the proposed approach a series of results is reported.

This paper theoretically and experimentally investigates the mutual coupling between two ports of dual slot-coupled circular microstrip antennas. Presented are the effects of feed configuration, slot length, slot offset from the circular disk center, circular disk radius and the dielectric constant of the feed substrate on the mutual coupling. Based on these results, the antenna with low mutual coupling was designed. The mutual coupling of under -35dB at the resonant frequency was obtained.

We describe a new water sensing system for optical fiber cable networks. This system consists of optical fibers, water sensors and an OTDR (Optical Time Domain Reflectometer). The water sensor contains material which swells on contact with water and bends the optical fiber. The OTDR monitors the optical loss increase caused by this fiber bending and determines its location. In this system it is very important to determine the loss increase caused by the water sensor in terms of the OTDR performance. Therefore, we clarified the relationship between the water sensor structure and the increase in loss. Based on this study, we fabricated a sensor which causes a 5dB loss increase. The measured value is very close to the calculated value.

A noninvasive method for measuring complex permittivity of biological tissues is proposed. The noninvasive method is based on an inverse scattering technique which employs an iterative procedure. The iterative procedure consists of solving an electric field integral equation using the method of moments and minimizing the square difference between calculated and measured scattered fields. Implementation of the noninvasive method requires the knowledge of the target shape, the incident and measured scattered fields. Based on the noninvasive method, a measuring system of complex permittivity is developed and its reliability is verified.

It is important to obtain a low coefficient sensitivity digital filter. This paper presents a new low coefficient sensitivity network structure that consists of a second order digital filter and a feedback path. This network structure is based on the effectiveness of the feedback path in an analog system. The coefficient sensitivity of the proposed digital filter can be control with the coefficient of the feedback path. Using this property, the digital filter with the low coefficient sensitivity is obtained. To add the feedback path makes the frequency response deviate from the characteristic of the original second order digital filter, but the deviation can be compensated with the other coefficients. A nonlinear optimization technique is employed to determine the coefficients of the digital filter. The proposed method is not effective only to narrow-band low-pass but wide-band low-pass filters.

From the standpoint of studying the biological effects of microwaves on human eyes, this paper numerically examines the specific absorption rate (SAR) inside the eyeball, using the finite-difference time-domain (FD-TD) method, which does not require very much computer storage. Two kinds of highly heterogeneous models constructed by us and Taflove's group are used to compute the SARs inside the eyeball for 1.5-GHz microwave exposure under the 1991 ANSI protection guideline. The SAR contour lines and the spatial distribution are shown inside the eyeball. Comparison is also made between the SARs for the two computation models.

The studies on the biological effects of ELF electric fields conducted in Japan are reviewed. Among international studies, they are characterized as the studies from the viewpoint of bioengineering. In early studies, the safety standard of high voltage transmission lines was determined by a distinct biological effect, i.e., the sensation of the spark discharge caused by electrostatic induction. In numerical analysis, the field coupling to both animal and human bodies became well understood. Some new measurement techniques were developed which enabled us to evaluate the field exposure on a human body. A system was developed to realize the chronic exposure of an electric field on mice and cats. An optical telemetry technique was developed to measure the physiological response of an animal when it was exposed to an electric field. An ion-current shuttle box was developed to investigate the behavioral change of a rat when it was exposed to an ion-current as well as an electric field. In animal experiments, a mechanism of sensing the field was investigated. The cause of the seasonal change of field sensitivity was found. In cases of chronic exposure, suppression of growth was suspected. In shuttle box studies, an avoidance behavior from an ion-current was quantified. To find whether there are any adverse or beneficial effects of the field exposure on human beings, further study is required to clarify the mechanisms of the biological effects.

In this paper, the fundamental characteristics of tactile recognition by electrical stimulus in order to develop a vision substitution system were described. The electrical stimulus pulse or DC voltage was applied at a touch board, and a conducting band which was connected to the ground level was fastened around a root of finger. First of all, the resistance of finger by the DC voltage was measured and the equivalent circuit of a finger was estimated. It was found that the most of resistance of this mechanism was concentrated at the contact of tip of finger and its value reached to MΩ order. And this resistance widely varied by the contact condition. The resistance of finger itself was relatively low and the contact resistance of band connectoin was about 30 kΩ. Total stray capacitance was about 26-62 nF, which was calculated by our experiments. Secondly, the minimum recognition voltage to applied stimulus pulse was measured by changing frequency, duty-ratio and voltage of pulse. It was found that the most sensitive pulse was in situation of that the frequency range was within from 60 Hz to 300 Hz, the duty-ratio of 20%, and the minimum sensitive voltage was about 13V. Lastly, this electrical stimulus pulse was applied to the touch Braille board. A touch Braille board was controlled by a computer (PC8801). In this system, an input letter from keyboard is translated to Braille code data by a computer automatically, which express the letter by the 6 points for the brind. And a Braille data is output at a touch board. By touching on the contact point of the touch board, a person can recognize Braille points by electrical stimulus. It was found that the Braille recognition by electrical stimulus pulse was available as same as it could be done by raised points.

This paper describes a novel technique to realize high performance digital sequential circuits by using Hopfield neural networks. For an example of applications of neural networks to digital circuits, a novel gate circuit, full adder circuit and latch circuit using neural networks, which have the global convergence property, are proposed. Here, global convergence means that the energy function is monotonically decreasing and each circulit always operates correctly independently of the initial values. Finally the several digital sequential circuits such as shift register and asynchronous binary counter are designed.