Topographic maps begin to be recognized as one of the major computational structures underlying neural computation in the brain. They provide dimension-reducing projections between feature spaces that seem to be established and maintained under the participation of selforganizing, adaptive processes. In this contribution, we investigate how well the structure of such maps can be replicated by simple adaptive processes of the kind proposed by Kohonen. We will particularly address the important issue, how the dimensionality of the input space affects the spatial organization of the resulting map.

High-speed digital land mobile communications suffer from frequency-selective fading due to a long delay difference. Several techniques have been proposed to overcome the multipath propagation problem. Among them, an adaptive array antenna is suitable for very high-speed transmission because it can suppress the multipath signal of a long delay difference significantly. This paper describes the LMS adaptive array antenna for frequency-selective fading reduction and a new diversity technique. First, we propose a method to generate a reference signal in the LMS adaptive array. At the beginning of communication, we use training codes for the reference signal, which are known at a receiver. After the training period, we use detected codes for the reference signal. We can generate the reference signal modulating a carrier at the receiver by those codes. The carrier is oscillated independently of the incident signal. Then, the carrier frequency of the reference signal is in general different from that of the incident signal. However, the LMS adaptive array works in such a way that the carrier frequency of the array output coincides with that of the reference signal. Namely, the frequency difference does not affect the performance of the LMS adaptive array. Computer simulations show the proper behavior of the LMS adaptive array with the above reference signal generator. Moreover, we present a new multipath diversity technique using the LMS adaptive array. The LMS adaptive array reduces the frequency-selective fading by suppressing the multipath components. This means that the transmitted power is not used sufficiently. We propose a multiple beam antenna with the LMS adaptive array. Each antenna pattern receives one of the multipath components, and we combine them adjusting the timing. Then, we realize the multipath diversity. In addition to the multipath fading reduction, we can improve a signal-to-noise ratio by the diversity technique.

The Batcher banyan network is well known as a non-blocking switching fabric. However, it is conflict free only when there is no packets for the same destination. To cope with the arbitrary combination of packets, an additional network or special control sequence which causes the increase of the hardware or performance degradation is required. A Batcher Double Omega network with Combining (BDOC) is an elegant solution of this problem. It consists of a Batcher sorter and two double sized Omega networks. Like in the Batcher banyan network, packets are sorted by the destination label in the Batcher sorter. In the first Omega network called the distributer, a packet is routed by a tag corresponding to the sum of the label at the output of the Batcher sorter and the destination label. In the second (Inverse) Omega network called the concentrator, the original destination label is used as the routing tag, and packets are routed without any conflict. The BDOC is useful for an interconnection network to connect processors and memory modules in multiprocessor. Unlike conventional multistage interconnection networks for multiprocessors, packets are transferred in a serial and synchronized manner. The simple structure of the switching element enables a high speed operation which reduces the latency caused by the serial communication. Using the pipelined circuit switching, the address and data packets share the same control signal, and the structure of the switching element is much simplified. Moreover, packets combining which avoids the hot spot contention is realized easily in the concentrator.

Principal Component Analysis (PCA) is a useful technique in feature extraction and data compression. It can be formulated as a statistical constrained maximization problem, whose solution is given by unit eigenvectors of the data covariance matrix. In a practical application like image compression, the problem can be solved numerically by a corresponding gradient ascent maximization algorithm. Such on-line algoritms can be good alternatives due to their parallelism and adaptivity to input data. The algorithms can be implemented in a local and homogeneous way in learning neural networks. One example is the Subspace Network. It is a regular layer of parallel artificial neurons with a learning rule that is completely homogeneous with respect to the neurons. However, due to the complete homogeneity, the learning rule does not converge to the unique basis given by the dominant eigenvectors, but any basis of this eigenvector subspace is possible. In many applications like data compression, the subspace is not sufficient but the actual eigenvectors or PCA coefficient vectors are needed. A new criterion, called the Weighted Subspace Criterion, is proposed, which makes a small symmetry-breaking change to the Subspace Criterion. Only the true eigenvectors are solutions. Making the corresponding change to the learning rule of the Subspace Network gives a modified learning rule, which can be still implemented on a homogeneous network architecture. In learning, the weight vectors will tend to the true eigenvectors.

Artificial neurons and neural networks have been shown to perform Principal Component Analysis (PCA) when gradient ascent learning rules are used, which are related to the constrained maximization of statistical objective functions. Due to their parallelism and adaptivity to input data, such algorithms and their implementations in neural networks are potentially useful in feature extraction and data compression. In the companion paper(9), two such learning rules were derived from two criteria, the Subspace Criterion and the Weighted Subspace Criterion. It was shown that the only solutions to the latter problem are dominant eigenvectors of the data covariance matrix, which are the basis vectors of PCA. It was suggested by a simulation that the corresponding learning algorithm converges to these eigenvectors. A homogeneous neural network implementation was proposed for the algorithm. The learning algorithm is analyzed here in detail and it is shown that it can be approximated by a continuous-time differential equation that is obtained by averaging. It is shown that the asymptotically stable limits of this differntial equation are the eigenvectors. The neural network learning algorithm is further extended to a case in which each neuron has a sigmoidal nonlinear feedback activity function. Then no parameters specific to each neuron are needed, and the learning rule is fully homogeneous.

This paper discusses the design, implementation, and performance of a bus-connected multiprocessor, called Presto, for a Rete-based production system. To perform a match, which is a major phase of a production system, a Presto match scheme exploits the subnetworks that are separated by the top two-input nodes and the token flow control at these nodes. Since parallelism of a production system can only increase speed 10-fold, the aim is to do so efficiently on a low-cost, compact bus-connected multi-processor system without shared memory or cache memory. The Presto hardware consists of up to 10 processisng elements (PEs), each comprising a commercial microprocessor, 4 Mbytes of local memory, and two kinds of newly developed ASIC chips for memory control and bus control. Hierarchical system software is provided for developing interpreter programs. Measurement with 10 PEs shows that sample programs run 5-7 times faster.

In recent years, the digitalization of transmission links, such as optical fibre cables, satellite links, and terrestrial microwave links, has been progressed rapidly in many countries. In addition, many types of digital studio equipment have been developed and TV programs can be produced or edited without any picture quality degradation by using such equipment, for example, digital VTR. A high-efficiency bit-reduction coding system is the most promising and effective means for this situation in terms of reducing the cost of digital transmission of TV programs with high picture quality. Considering this background, a new digital coding system has been developed, which makes it possible to transmit up to 4 NTSC TV programs simultaneously over a single DS3 45Mbps link including two high quality sound channels and one 64kbps ancillary data channel for each TV program. The principal bit-reduction technique employed is 2 dimensional intraframe WHT (Walsh Hadamard Transform) coding, which gives higher coding performance for composite TV signals than DCT (Discrete Cosine Transform) coding. In order to attain high picture quality at around 8Mbps for 4 channel transmission, a 3 dimensional adaptive quantization cube which reflects human visual perception sufficiently is employed in the intraframe WHT coding scheme. The hardware has been made compact like a home use VTR. In this paper, first, the algorithm of the coding scheme developed for the coding system is presented, and then the system configuration and its basic coding performance are described.

This paper presents an automatic creation method of 3D facial models which are needed for facial image generation by 3D computer graphics. A 3D facial model of a specific person is obtained from just the front and side view images without any human operation. The method has two parts; feature extraction and generic model modification. In the feature extraction part, the regions or edges which express the facial features such as eyes, nose, mouth or chin outline are extracted from the front and side view images. A generic head model is then modified based on the position and shape of the extracted facial features in the generic model modification part. As a result, a 3D model for persons is obtained. By using the specific model and the front and side view images, texture-mapped facial images can be generated easily.

Networks in this paper consist of non-commensurate transmission lines with branches and branching resistors at junctions. When signals on a transmission line are divided multiple ways at the junctions of branched lines, multiple reflection waves occur by the impedance mismatching. For the analysis of multiple reflections and network design, lattice diagrams have been used so far. However, the expansions of network transfer functions provide an easier way for the same purpose as in the case of lattice diagram. The output transient responses can be directly calculated from the expansions of network transfer functions or can be numerically calculated by software such as the fast Laplace transform. Therefore, once the network transfer functions are given, calculation of transient responses can be carried out quite easily. In this paper, the expansions of network transfer functions have been derived with respect to delay elements ξi=exp(-sτi) by formularizing the propagation of multiple reflection waves, and then the multi-variable rational network transfer functions have been obtained from the expansions. As an example, a 3-port transmission line network with normalized characteristic impedances 1, 1, 6 and normalized branching resistors 1/23, 1/23, 126/23 has been taken up. As the terminal resistances at output ports can be determined from the relation of the first arriving wave to the steady state, the design of 3-port transmission line networks which will furnish output waveforms similar to the waveform of the input within given tolerances has been considered. The output waveforms have been calculated for pure terminal resistances and for the pure terminal resistances plus parasitic parallel capacitances.

We propose a new distributed signal (analog or digital) transmission system which has the immunity against the noisy channel. An information signal in transmitter is distributed by distributor and the distributed signal is transmitted. Received signal is reconstructed by the inverse distributor in receiver. In this system, an impulsive interference noise which disturbs the transmission signal in the channel passes decoder only, and this interference noise is distributed by the inverse distributor while the transmitted signal is reconstructed. Some appended signals make it possible to estimate the noise components which inversely distributed with the Fourier transformation as the distributor. Basing upon this principle, the transmission system will have an ability to suppress the impulsive interference, and the channel will have high noise immunity. The construction of receiver which can eliminate the impulsive noise is derived.

Binary Decision Diagrams (BDDs) and Shared Binary Decision Diagrams (SBDDs), which are improved BDDs, are useful for implementing VLSI logic design systems. Recently, these representations, which are graph representations of Boolean functions, have become popular because of their efficiency in terms of time and space. The forms of the BDD vary with the order of the input variables though they represent the same function. The size of the graphs greatly depends on the order. The variable ordering algorithm is one of the most important issues in the application of BDDs. In this paper, we consider methods which reduce the graph size by reordering input variables on a given BDD with a certain variable order. We propose the Minimum-Width Method which gives a considerably good order in a practicable time and space. In the method, the order is determined by width of BDDs as a cost function. In addition, we show the effect of combining our method with the local search method, and also describe the improvement using the threshold. Experimental results show that our method can reduce the size of BDDs remarkably for most examples. The method needs no additional information, such as the topological information of the circuit. The results can be a measure for evaluation of other ordering methods.

This paper presents a survey on bicriteria network optimization problems. When there are two conflicting criteria that evaluate the solution, the bicriteria optimization is to find a solution for which these criteria are both acceptably satisfied. Standard approaches to these problems are to combine these two criteria into an aggregated single criterion. Among such problems, this paper first deals with the case in which the aggregated objective function, denoted h(f1(x), f2(x)), is convex in original two objectives f1(x) and f2(x), and, as its special case, it reviews a strongly polynomial algorithm for the bicriteria minimum-cost circulation problem. It then discusses the case in which h is concave and demonstrates that a parametric approach is effective for this case. Several interesting applications in network optimization that belong to this class are also introduced. Finally we deal with the minimum range problems which seek to find a solution such that weights of the components used in the solution are most uniform. We shall present efficient algorithms for solving these problems arised in network optimization.

We have developed a new model to analyze the thermal failure mechanism due to electrical-over-stress (EOS) for two-dimensional planar pn-junction structures where the failure power is proportional to about 1/5 power of the failure time. We adopted a pseudo two-dimensional numerical simulation method where a pn-junction diode is divided into small elements and represented by a circuit network composed of many minute resistors and diodes. The failure mechanism studied by Wunsch and Bell, that is one of many studies for one-dimensional pn-diodes, is not valid for the case of two-dimensional pn-junction, such as a planar type junction. On the contrary, the failure mechanism was found to be much correlative with the junction structure, especially the impurity concentration in the substrate in the two-dimensional case. When the impurity concentration in the substrate is high enough (e.g. Nsub1017[cm-3]), the breakdown occurs at the whole junction. The heat transfer is one-dimensional and the failure power is proportional to about 1/2 power of the failure time, which is well known results reported by many researchers: e.g. Wunsch &Bell. On the other hand, when the impurity concentration in the substrate is low enough (e.g. Nsub1016[cm-3]), the breakdown occurs locally at the junction edge. The heat transfer is two-dimensional and the failure power is in proportion to about 1/5 power of the failure time.

We have developed an efficient general-purpose two-dimensional device simulation system which consists of a solver, and pre- and post-processors. This system can easily handle any complicated device having a non-rectangular shape. It can also be applied to compound semiconductor devices with heterojunctions, including optical devices such as laser diodes. In order to handle any device, a new program for construction of device geometry is developed as a preprocessor. It has an efficient graphic interface to reduce the time required to input data for simulations, which is a very time consuming task for complicated devices. A new efficient data structure representing device geometry is introduced in the program. During postprocessing, any physical quantity can be displayed on the multi-window screen. In addition, a general-purpose solver for basic semiconductor equations is implemented in the system. Using this system, any device can be successfully analyzed in a unified manner and the turn-around time for the simulation is significantly reduced.

Binaural effects in two measures are studied. One measure is the detectable limen of click sounds under lateralization of diotic or dichotic noise signals, and the other is phoneme articulation score under localization or lateralization of speech and noise signals. The experiments use a headphones system with listener's own head related transfer function (HRTF) filters. The HRTF filter coefficients are calculated individually from the impulse responses due to the listener's HRTF measured in a slightly sound reflective booth. The frequency response of the headphone is compensated for using an inverse filter calculated from the response at the subject's own ear canal entrance point. Considering the speech frequency band in tele-communication systems is not sufficiently wide, the bandwidth of the HRTF filter is limited below 6.2 kHz. However, the experiments of the localization simulation in the horizontal plane show that the sound image is mostly perceived outside the head in the simulated direction. Under simulation of localization or lateralization of speech and noise signals, the phoneme articulation score increases when the simulation spatially separates the phonemes from the noise signals while the total signal to noise ratio for both ears is maintained constant. This result shows the binaural effect in speech intelligibility under the noise disturbance condition, which is regarded as a part of the cocktail party effect.

The development of computers capable of handling complex objects requires nonverbal interfaces that can bidirectionally mediate nonverbal communication including the gestures of both people and computers. Nonverbal expressions are poweful media for enriching and facilitating humancomputer interaction when used as interface languages. Four gestural modes are appropriate for human-computer interaction: the sign, indication, illustration and manipulation modes. All these modes can be conveyed by a generalized gesture interface that has specific processors for each mode. The basic component of the generalized gesture interface, a gesture dictionary, is proposed. The dictionary can accept sign and indicating gestures in which postures or body shapes are significant, pass their meaning to a computer and display gestures from the computer. For this purpose it converts body shapes into gestural codes by means of two code systems and, moreover, it performs bidirectional conversions of several gesture representations. This dictionary is applied to the translation of Japanese into sign language; it displays an actor who speaks the given Japanese sentences by gesture of sign words and finger alphabets. The performance of this application confirms the adequacy and usefulness of the gesture dictionary.

To realize a highly efficient small antenna, high-Tc superconductors are adopted to fabricate both a self-resonating helical radiator and a quarter-wave matching circuit. The actual gain and bandwidth measured at 478 MHz using a 1/45-wavelength radiator were respectively 1.5 dBi and 0.35%, indicating that this type of antenna has a high radiation efficiency and a fairly wide bandwidth. It is also confirmed through experiments and theoretical simulations that a decrease in the surface resistance of the radiator more effectively improves the radiation efficiency than a decrease in the surface resistance of the matching circuit.

A new MOS linear operational transconductance amplifier (OTA) for the up-to-4 MHz range OTA-C filters is proposed. The proposed OTA is designed using a new linearizing technique based on bias-current modulation, to compensate nonlinearities in the transfer characteristic of the conventional current-source-biased source-coupled pair. The design and SPICE simulation are presented in detail, assuming the implementation by the typical p-well CMOS process. The simulation of a 3.58 MHz OTA-C band-pass filter built with the proposed OTAs showed close agreement with the desired performance.

The nonlinear optical properties of organics with unsaturated bonds were compared with those of inorganics including semiconductors and dielectrics. Because of the mesomeric effect, namely quantum mechanical resonance effect among configurations, aromatic molecules and polymers have larger optical nonlinear parameters defined as δ(n)X(n)/(X(1))n both for the second (n2) and third-order (n3) nonlinearities. Experimental results of ultrafast nonlinear response of conjugated polymers, especially polydiacetylenes, were described and a model is proposed to explain the relaxation processes of photoexcitations in the conjugated polymers. Applying the model constructed on the basis of the extensive experimental study, we propose model polymers to obtain ultrafast resonant optical nonlinearity.

The VSTEP concept and its practical application in the form of an LED-type pnpn-VSTEP demonstrating low power consumption through electro-photonic operational modes are both shown. Further, with focus primarily on the new laser-mode VSTEP with high-intensity light output and narrow optical beam divergence, the design features such as threshold gain and optical absorptivity, device fabrication, and characteristics are explained. The possibility of ultimate performance based mainly on electrical to optical power conversion efficiency, important from the application viewpoint of optical interconnection, are also discussed. Also, as two examples of functional optical interconnection achieved by VSTEP, serial-to-parallel data conversion and optical self-routing switches are shown. Finally, future opto-electronic technologies to be developed for two-dimensionally integrable surface-type optical semiconductor devices, including the VSTEP, are discussed.