Optical recording has been performed successfully by the preirradiation of light upon the precursor of poly (arylene vinylene) conducting polymers such as poly (p-phenylene vinylene) (PPV) and poly (1,4-naphthalene vinylene) (PNV) and subsequent thermal treatment. The effect has been tentatively interpreted in terms of the deterioration of the irradiated area of the precursor polymer in which polymerization is suppressed. Furthermore, an orange electroluminescent (EL) diode utilizing PNV has been demonstrated for the first time and the EL properties of PNV are discussed in comparison with those of EL diode utilizing PPV. The EL emission of these two devices are discussed in terms of radiative recombination of the singlet polaron exciton formed by the injection of electrons and holes, the difference of effective conjugation length and the interchain transfer of polaron excitons.

We fabricated junctions with a porphyrin polyimide (PORPI) monolayer, and then investigated the electron transport properties of the junctions from the current-voltage (I-V) and d2V/dI2-V measurements. Polyimide LB films without porphyrin were used as tunneling barriers. One large peak was seen at a voltage around 1.9 V, due to the excitation of electron transitions in PORPI molecules, whereas a step structure was not observed in the I-V characteristic.

Truncated sum (TSUM for short) is useful for MV-PLA's realization. This paper introduces a new class of multiple-valued logic functions that are expressed by truncated sum, differential product (DPRODUCT for short), NOT and variables, where TSUM (x, y)min (xy, p1) and DPRODUCT (x, y)max (xy(p1), 0) is newly defined as the product that is derived by applying De Morgan's laws to TSUM. We call the functions T-functios. First, this paper clarifies that a set of T-functions is not a lattice. It clarifies that Lukasiewicz implication can be expressed by TSUM and NOT. It guarantees that a set of p-valued T-functios is not complete but complete with constants. Next, the speculations of the number of T-functions for less than ten radixes are derived. For eleven or more radix p, a speculation of the number of p-valued T-functions is shown. Moreover, it compares the T-functions with B-functions. The B-functions have been defined as the functions expressed by MAX, MIN, NOT and variables. As a result, it shows that a set of T-functions includes a set of B-functions. Finally, an inclusion relation among these functional sets and normality condition is shown.

The optical waveguides containing phthalocyanine as an optically active material were fabricated and transmission properties were investigated experimentally and numerically. The positive refractive index change was observed in the glass waveguide with a vanadyl phthalocyanine thin film as a top layer. The thermal influence on refractive index change was estimated by surface plasmon measurements.

We discuss estimation error as a basic problem in formant estimation in the analysis of speech of very short-time duration in the glottal closure of the vowel. We also show in our simulation that good estimation of the first formant is almost impossible with the ordinary method using a waveform cutting. We propose a new method in which the cut waveform, as a discontinuous function of finite time, is mapped to a continuous function defined in the whole time domain; and we show that using this method, the estimation accuracy for low frequency formants can be greatly improved.

It is an important problem whether or not we can reject the disturbances from distributed parameter circuit. In order to analyze this problem structurally, it is necessary to investigate the basic equation of distributed parameter circuit in the framework of state space. Since the basic equation has two parameters for time and space, the state value belongs to an infinite-dimensional space. In this paper, the disturbance-rejection problems with incomplete state feedback and/or incomplete state feedback and feedforward for infinite-dimensional systems are studied in the framework of geometric approach. And under certain assumptions, necessary and/or sufficient conditions for these problems to be solvable are proved.

Wave digital filters are a class of digital filters. They are equivalent to commensurate transmission line circuits synthesized with uniform, lossless, and commensurated transmission lines. In order to extend their applications to physical wave phenomena including quantum electronics, it is necessary to consider a generalized distributed line whose velocity of energy flow has frequency characteristics. This paper discusses a generalized distributed circuit, and we obtain two types of lines, lossless and cut-off. In order to analyze these lines, we discuss signal flow graphs of steady state voltage and current. The reflection factors we obtain here are the same as that for an active power or a diagonal element of a scattering matrix, which is zero in conjugate matching. By using this reflection factor, we obtain band-pass filters synthesized with the cut-off lines. We also describe an analysis method for nonuniform line related to Riccati differential equation.

In the band-limited signal space, the mutual relation between continuous time signal and discrete time signal is expressed by the sampling theorem of Whittaker-Someya-Shannon. This theorem consists of an orthonormal expansion formula using sinc functions. In that formula, the expansion coefficients are identical to the sample values of signals. In general, the bandlimited signal space is not always suited to model the signals in nature. The authors have proposed a new model for signal processing based on finite times continuously differentiable functions. This paper aims to complete the sampling theorem for the spline signal spaces, which corresponds to the sampling theorem of Whittaker-Someya-Shannon in the band-limited signal space. Since the obtained sampling theorem gives the simplest representation of signals, it is considered to be the most fundamental characterization of spline functions used for signal processing. The biorthonormal basis derived in this paper is considered to be a system of delta functions at sampling points with some continuous differentiability.

This paper presents techniques for generating the input patterns for locating logic design errors (PLE's) by Boolean function manipulation based on binary decision diagrams (BDD's). One PLE has one Boolean variable X or and constant values. A primary output of a correct circuit takes value X, while the designed circuit takes either 0 or 1. By using PLE's, the X-algorithms locate single or multiple logic design errors in a combinational circuit. Although PLE's play the most important role in the X-algorithms, the condition under which PLE's exist has not been formalized. This paper gives a formal analysis on the existence condition of PLE's. It is shown that the condition is always satisfied by incorporating another type of PLE. From the condition, an implicit representation of PLE's is derived. In addition, two kinds of approaches are presented for generating PLE's by Boolean function manipulation based on BDD's. One is an approach for generating all the existing PLE's. The other is a heuristic approach to obtain a limited number of PLE's in a short time. Both approaches generate PLE's including don't cares. Incorporating them, a compact representation of PLE is achieved. Experimental results have shown the compactness of the proposed representations and the availability of the pattern generation techniques.

Reduction of the complexity of the NLMS algorithm has received attention in the area of adaptive filtering. A processing cost reduction method, in which the component of the weight vector is updated when the absolute value of the sample is greater than or equal to the average of the absolute values of the input samples, has been proposed. The convergence analysis of the processing cost reduction method has been derived from a low-pass filter expression. However, in this analysis the effect of the weignt vector components whose adaptations are skipped is not considered in terms of the direction of the gradient estimation vector. In this paper, we use an arbitrary value instead of the average of the absolute values of the input samples as a threshold level, and we derive the convergence characteristics of the processing cost reduction method with arbitrary threshold level for zero-mean white Gaussian samples. From the analytical results, it is shown that the range of the gain constant to insure convergence and the misadjustment are independent of the threshold level. Moreover, it is shown that the convergence rate is a function of the threshold level as well as the gain constant. When the gain constant is small, the processing cost is reduced by using a large threshold level without a large degradation of the convergence rate.

When measuring the ejection fraction for the evaluation of the ventricular pumping function by means of the thermodilution technique, the slow response a conventional thermistor has caused it to be considered unsuitable, and fast thermistors have been proposed as an alternative. However, in this paper we propose improving the time-domain response of a conventional thermistor using a signal processing technique composed of a series of first-order high-pass filters which is known as the natural observation system. We considered the rise time of the thermistor in response to a step temperature change to effect correction for the measurement of the ejection fraction. The coefficients of the natural observation system were calculated by minimizing the square error between the step-response signal of the thermistor and the band-limited reference signal. In an experiment using a model ventricle, the thermodilution curve obtained from a conventional thermistor was improved using the proposed technique, thus enabling successful measurement of the ejection fraction of the ventricles.

The performance of selection diversity combined with decision feedback equalizer for reception of TDMA carriers is investigated in this paper. The second generation digital land mobile communication systems standardized in the U.S., Japan, and Europe employ TDMA carriers at transmission bit rates up to several hundreds kbit/s. In order to provide higher quality of mobile communications services to the user with employing TDMA carriers, the systems would require both diversity and equalization techniques to combat attenuation of received signal power level due to Rayleigh fading and intersymbol interference resulting from time-variant multipath fading, respectively. This paper proposes a novel integration method of selection diversity and decision feedback equalization techniques which provides the better bit error rate performance than that for the conventional selection diversity method with decision feedback equalizer. The feature of proposed method is that selection diversity and decision feedback equalization techniques are integrated so as to interwork each other. We call the proposed method by the Decision Feedback Diversity with Decision Feedback Equalizer. The detailed algorithm of the proposed method is first presented, and then the system parameters for the method are evaluated based on the computer simulation results. Finally the computer simulation results for the performance of the proposed method are presented and compared to those for the conventional Selection Diversity with Decision Feedback Equalizer and the conventional Dual Diversity Combining and Equalization method under the typical mobile radio environments, in order to demonstrate the validity of the proposed method.

This letter proposes a high speed multifiber connector assembly method, which uses UV-curable adhesive and which does not require a polishing process, thus reducing the connector assembly time. It is confirmed that the assembly time can be reduced to less than half the time required with the conventional assembly method. The multifiber connectors assembled using this method have a low connection loss and stable mechanical characteristics.

We develop a convergence theory of the simple genetic algorithm (SGA) for two-bit problems (Type I TBP and Type II TBP). SGA consists of two operations, reproduction and crossover. These are imitations of selection and recombination in biological systems. TBP is the simplest optimization problem that is devised with an intention to deceive SGA into deviating from the maximum point. It has been believed that, empirically, SGA can deviate from the maximum point for Type II while it always converges to the maximum point for Type I. Our convergence theory is a first mathematical achievement to ensure that the belief is true. Specifically, we demonstrate the following. (a) SGA always converges to the maximum point for Type I, starting from any initial point. (b) SGA converges either to the maximum or second maximum point for Type II, depending upon its initial points. Regarding Type II, we furthermore elucidate a typical sufficient initial condition under which SGA converges either to the maximum or second maximum point. Consequently, our convergence theory establishes a solid foundation for more general GA convergence theory that is in its initial stage of research. Moreover, it can bring powerful analytical techniques back to the research of original biological systems.

Antenna selection diversity is an effective method to achieve both better transmission performance and compact circuit implementation in TDMA portable radio communications. However, diversity performance in fast fading environments is insufficient. This paper proposes a novel predictive antenna selection diversity scheme, PASD, which improves the diversity performance for higher fading rates. In PASD, received signal power for the assigned data slot is predicted from previously measured data. Thus, selection errors due to the receiving power changes caused by fast Rayleigh fading can be effectively avoided. An experimental result for a 3-ch TDMA system with a frame duration of 20ms shows that the diversity gain was increased by 1.3dB over the conventional method for a fading rate of 40Hz. PASD is also shown to have improved diversity performance against cochannel interference.

This paper describes the general conditions for perfect signal reconstruction in adaptive blocksize MDCT. MDCT, or modified Discrete Cosine Transform, is a method in which blocks are laid to overlap each other. Because of block overlapping, some consideration must be paid to reconstructing the signals perfectly in adaptive blocksize schemes. The perfect reconstruction conditions are derived by considering the reconstruction signals, on a segment by segment basis. These conditions restrict the analysis/synthesis windows in the MDCT formula. Finally, this paper evaluates two examples of window sets, including windows used in the ISO MPEG audio coding standard.

Recently, many researches on associative memories have been made a lot of neural network models have been proposed. Bidirectional Associative Memory (BAM) is one of them. The BAM uses Hebbian learning. However, unless the traning vectors are orthogonal, Hebbian learning does not guarantee the recall of all training pairs. Namely, the BAM which is trained by Hebbian learning suffers from low memory capacity. To improve the storage capacity of the BAM, Pseudo-Relaxation Learning Algorithm for BAM (PRLAB) has been proposed. However, PRLAB needs long learning epochs because of random initial weights. In this paper, we propose Quick Learning for BAM which greatly reduces learning epochs and guarantees the recall of all training pairs. In the proposed algorithm, the BAM is trained by Hebbian learning in the first stage and then trained by PRLAB. Owing to the use of Hebbian learning in the first stage, the weights are much closer to the solution space than the initial weights chosen randomly. As a result, the proposed algorithm can reduce the learning epocks. The features of the proposed algorithm are: 1) It requires much less learning epochs. 2) It guarantees the recall of all training pairs. 3) It is robust for noisy inputs. 4) The memory capacity is much larger than conventional BAM. In addition, we made clear several important chracteristics of the conventional and the proposed algorithms such as noise reduction characteristics, storage capacity and the finding of an index which relates to the noise reduction.

Results of a DC motor driving test with a power sent by a microwave and extracted with a rectenna array are reported. No significant difference has been observed in the output DC power from the rectenna array between a motor load and a resistive load. Mechanical output could be extracted from the received microwave power with an efficiency of 26%.

This paper proposes a new method to determine the shape of a surface by learning the mapping between three image irradiances observed under illumination from three lighting directions and the corresponding surface gradient. The method uses Phong reflectance function to describe specular reflectance. Lambertian reflectance is included as a special case. A neural network is constructed to estimate the values of reflectance parameters and the object surface gradient distribution under the assumption that the values of reflectance parameters are not known in advance. The method reconstructs the surface gradient distribution after determining the values of reflectance parameters of a test object using two step neural network which consists of one to extract two gradient parameters from three image irradiances and its inverse one. The effectiveness of this proposed neural network is confirmed by computer simulations and by experiment with a real object.

In this paper, we develop a unified synthesizing approach for the cloning templates of Cellular Neural Networks (CNNs). In particular, we shall consider the case when the signal processing problem is complex, and a multilayered CNN with time-variant templates is necessary. The method originates from the existence of correspondence between the cloning templates of Cellular Neural Network and its discrete counterpart, Discrete-Time Cellular Neural Network (DTCNN), in solving a prescribed image processing problem when time-variant templates are involved. Thus, one can start with calculating the cloning templates from DTCNN, and then translating the cloning templates to those for CNN operations. As a result, the mathematical tools being used in the synthesis of Discrete-time Cellular Neural Network can also be applied to the analog type Cellular Neural Network. This inevitably helps to simplify the design problem of CNN for signal processing. Examples akin to contour drawing and parallel thinning are shown to illustrate the merits of our proposed method.