The operation scheduling is an important subtask in the automatic synthesis of digital systems. Many greedy heuristics have been proposed for the operation scheduling, but they cannot find the globally best schedule. In this paper we present an algorithm to construct near optimal schedules. The algorithm combines characteristics of simulated annealing and neural networks. The neural network used in our scheduling algorithm is similar to that proposed by Hellstrom et al. However, while the problems of Refs. [11] and [12] have a single type of constraint, the problem considered in this paper has three types of constraints. As the result, the energy function of the proposed neural network is given by the weighted sum of three energy functions. To minimize the weighted sum of two or more energy functions, conventional methods try to find a good set of weights using a try and error method. Our algorithm takes a different approach than these methods. Results of the experiments show that the proposed algorithm can be used as an alternative heuristic for solving the operation scheduling problem. In addition, the proposed algorithm can exploit the inherent parallelism of the neural network.

Recent works have shown that the size reduction of printed dipole antennas was possible thanks to a proper shaping of the radiating element. Following the same idea (choice of suitable shape), a shortened slot fed patch antenna exhibiting two step discontinuities, is described, analysed and optimized with a simple transmission line model. The shortening ratio (ρ) can reach 80% for matched antenna, printed on a substrate with a low dielectric constant (εr=2.2). The calculated results of input impedance are validated by experiment.

This paper presents a new Adaptive Convergence Factor (ACF) algorithm without the damping parameter adjustment acoording to the input signal and/or the composition of the filter system. The damping parameter in the ACF algorithms has great influence on the convergence characteristics. In order to examine the relation between the damping parameter and the convergence characteristics, the normalization which is realized by the related signal terms divided by each maximum value is introduced into the ACF algorithm. The normalized algorithm is applied to the modeling of unknown time-variable systems which makes it possible to examine the relation between the parameters and the misadjustment in the adaptive algorithms. Considering the experimental and theoretical results, the optimum value of the damping parameter can be defined as the minimum value where the total misadjustment becomes minimum. To keep the damping parameter optimum in any conditions, the new ACF algorithm is proposed by improving the invariability of the damping parameter in the normalized algorithm. The algorithm is investigated by the computer simulations in the modeling of unknown time-variable systems and the system indentification. The results of simulations show that the proposed algorithm needs no adjustment of the optimum damping parameter and brings the stable convergence characteristics even if the filter system is changed.

We are developing multimodal man-machine interfaces through which users can communicate by integrating speech, gaze, facial expressions, and gestures such as nodding and finger pointing. Such multimodal interfaces are expected to provide more flexible, natural and productive communications between humans and computers. To achieve this goal, we have taken the approach of modeling human behavior in the context of ordinary face-to-face conversations. As the first step, we have implemented a system which utilizes video and audio recording equipment to capture verbal and nonverbal information in interpersonal communications. Using this system, we have collected data from a task-oriented conversation between a guest (subject) and a receptionist at company reception desk, and quantitatively analyzed this data with respect to multi-modalities which would be functional in fluid interactions. This paper presents detailed analyses of the data collected: (1) head nodding and eye-contact are related to the beginning and end of speaking turns, acting to supplement speech information; (2) listener responses occur after an average of 0.35 sec. from the receptionist's utterance of a keyword, and turn-taking for tag-questions occurs after an average of 0.44 sec.; and (3) there is a rhythmical coordination between speakers and listeners.

In this paper, we propose a learning fuzzy network (LFN) which can be used to implement most of fuzzy logic functions and is much available for hardware implementations. A learning algorithm largely borrowed from back propagation algorithm is introduced and used to train the LFN systems for several typical fuzzy logic problems. We also demonstrate the availability of the LFN hardware implementations by realizing them with CMOS current-mode circuits and the capability of the LFN systems by testing them on a benchmark problem in intelligent control-the inverted pendulum system. Simulations show that a learning fuzzy network can be realized with the proposed LFN system, learning algorithm, and hardware implementations.

We propose a stabilization method of unstable periodic orbits embedded in a chaotic attractor of continuous-time system by using discrete state feedback controller. The controller is designed systematically by the Poincar mapping and its derivatives. Although the output of the controller is applied periodically to system parameter as small perturbations discontinuously, the controlled orbit accomplishes C0. As the stability of a specific orbit is completely determined by the design of controller, we can also use the method to destabilize a stable periodic orbit. The destabilization method may be effectively applied to escape from a local minimum in various optimization problems. As an example of the stabilization and destabilization, some numerical results of Duffing's equation are illustrated.

This paper describes the imaging method for a human forearm in the microwave transmission CT at 3GHz. To improve the spatial resolution, the correction method of the diffraction effects is adopted and the high directivity antennas are used. A cross-sectional image of the human forearm is obtained in vivo.

This paper proposes two algorithms for defining a routing domain in multiclass-of-service networks. One an off-line-based method, whose objective is to optimize dynamic routing performance by using precise knowledge on the traffic levels. The algorithm of the proposed method takes into account the random nature of the traffic flow, which is not considered in the network flow approach. The proposed method inherits the conceptual simplicity of the network flow approach and remains applicable to large and complex networks. In simulation experiments, the proposed off-line-based method performs better than the method based on the network flow approach, but has a similar the computation time requirement. The other method proposed here is an on-line-based method for application to B-ISDNs, where precise traffic data is not expected to be available. In this method, the routing domain is defined adaptively according to the network performance (call-blocking probability) measured in real-time. In simulation experiments, the performance of this method is comparable to that of the off-line-based method--especially when highly efficient dynamic routing is used. This paper also derives and describes methods for approximating the implied costs for multiclass-of-service networks. The approximations are very useful not only for off-line-based routing domain definition (RDD) methods but also for other kinds of network controls or optimal network dimensioning based on the concept of revenue optimization.

In coherent optical space communication systems, the phase noise generated from high power laser diodes and the polarization axis mismatch between transmitter and receiver are the serious problem. In this paper, a novel coherent optical space communication system, called optical polarization azimuth modulation (POLAM)/heterodyne detection system is newly proposed, and its system performance is theoretically investigated. It is clarified that the POLAM system can perfectly remove the laser phase noise, is actually insensitive to the polarization axis mismatch, and can provide the remarkable performance improvement compared to a conventional optical frequency modulation system.

In this study, a ring of simple chaotic circuits coupled by inductors is investigated. An extremely simple three-dimensional autonomous circuit is considered as a chaotic subcircuit. By carrying out circuit experiments and computer calculations for two, three or four subcircuits case, various synchronization phenomena of chaos are confirmed to be stably generated. For the three subcircuits case, two different synchronization modes coexist, namely in-phase synchronization mode and three-phase synchronization mode. By investigating Poincar map, we can see that two types of synchronizations bifurcate to quasi-synchronized chaos via different bifurcation route, namely in-phase synchronization undergoes period-doubling route while three-phase synchronization undergoes torus breakdown. Further, we investigate the effect of the values of coupling inductors to bifurcation phenomena of two types of synchronizations.

We reported that a competitive learning neural network had the ability of self-organization in the classification of questionnaire survey data. In this letter, its self-organized learning was evaluated by means of mutual information. Mutual information may be useful to find efficently the network which can give optimal classification.

This paper describes a SQUID magnetometer and the measurement of small signals. It also describes the current state of SQUID technology developed in the SSL project.

This paper describes a parameter extraction system that can easily accommodate many MOSFET models. The model-adaptability is contributed by tow factors; a model-adaptable initial value estimation technique and an environment which stores and reuses extraction procedures. A designer can easily develop an extraction procedure for a new MOSFET model by modifying a procedure for another MOSFET model developed previously. We have verified that the system is suitable for major SPICE models.

This letter addresses stability problems of interval matrices stemming from robustness issues in control theory. A quick overview is first made pertaining to methods to obtain stability conditions of interval matrices, putting particular emphasis upon one of them, regularity condition approach. Then, making use of this approach, several new stability criteria, for both Hurwitz and Schur stability, are derived.

We report here a pulsed lightwave frequency synthesizer system that is composed of a pulsed lightwave sweep frequency generator and a tracking generator. The key advance in the sweep generator is the use of a dynamically gain controlled EDFA. The combination of feedback and feed forward dynamic gain control effectively compensates EDFA gain fluctuation and equalizes fiber loop loss so that the initial pulse wave form and amplitude is retained in the loop at large circuit numbers. Over 1000 pulsed lightwave frequencies are synthesized in 250MHz steps by the sweep generator. Almost flat response (0.55dB variation) is realized up to 240GHz. The power spectrum decreases by 67% (1.7dB down) at 250GHz. The peak level of the pulses output from the loop is about -4dBm. Tracking generator and total synthesizer system performance are evaluated by (a) beat frequency between the tracking generator and the master lightwave source, (b) beat frequency between two tracking generators, and (c) a frequency chain between the master lightwave source and another HCN stabilized lightwave source via the synthesizer system. A continuous lightwave frequency locked to a frequency selected from the pulsed sweep frequency signal is demonstrated at over 200GHz to have an instability of 5MHz. Absolute accuracy of the lightwave frequency emitted from the synthesizer system is about 10MHz. Therefore, the relative accuracy of the lightwave frequency is as high as 510-8.

A self-induced-transparent (SIT) system that takes advantage of morphology dependent resonances (MDR's) in a Mie-sized microsphere doped with a resonant material is proposed. The present system is doubly resonant: one has microscopic origin (the two-level system), while the other has macroscopic origin (the MDR). In this geometry, owing to the feedback action of MDR's, the pulse area can be much expanded, and thus the electric-field amplitude of the incident pulse can be reduced substantially compared with the conventional one-way SIT propagation. Theoretical results that incorporate dephasing due to structural imperfections are shown.

Voting is a general way of achieving mutual exclusion and synchronization in distributed systems with replicated data. In centralized voting protocols, a requesting node, which works as a central controller, exchanges messages in order to collect votes from other nodes. This paper proposes decentralized voting protocols, in which all nodes execute the same protocol and reach the same result in a decentralized and autonomous way. When a decentalized voting protocol is implemented by using one-round message exchange, it requires n(n1) messages, where n is the number of nodes. The number of messages can be reduced by using multiple-round message exchange. The paper describes the computation in each node in the form of the finite state automaton, and gives communication structures for it. It is shown that kn(n1/k1) messages are enough when messages are exchanged in k rounds.

This paper proposes a practical training algorithm for artificial neural networks, by which both the optimally pruned model and the optimally trained parameter for the minimum prediction error can be found simultaneously. In the proposed algorithm, the conventional information criterion is modified into a differentiable function of weight parameters, and then it is minimized while being controlled back to the conventional form. Since this method has several theoretical problems, its effectiveness is examined by computer simulations and by an application to practical ultrasonic image reconstruction.

Circuit design techniques for linearizing adaptively biased differential pairs are described. An emitter-and source-coupled pair is adaptively biased by a squaring circuit to linearize its transconductance, one of whose inputs is divided by resistors. An input signal for a differential pair or a squaring circuit is set to an adequate amplitude by a resistive divider without sacrificing linearity. Therefore, a differential pair is biased by the output current of a squaring circuit and they are coupled directly. There are three design techniques for squaring circuits. One is the transistor-size unbalance technique. Another is the bias offset technique. A third is the multitail technique. The bipolar and MOS squaring circuits discussed in this paper were proposed by the author previously, and consist of transistor-pairs with different transistor size (i.e., the emitter areas or gate W/L values are different), transistor-pairs with the same bias offset, or a multitail cell(i.e., a triple-tail cell or quadritail cell). Several kinds of squaring circuits consisting of such transistor-pairs are applied to produce the quadratic bias currents for compensating the nonlinearity of an emitter-and source-coupled pair. Therefore, four circuits using emitter-coupled pairs with adaptive-biasing current and four circuits using source-coupled pairs with adaptive-biasing current are proposed and analyzed in depth. Furthermore, a circuit configuration for low voltage operation is also introduced and verified with bipolar transistor-arrays on a breadboard.

A 10-kW (53V/200A), forced-air-cooled DC-DC converter has been developed for fuel cell systems. This converter uses new high-voltage bipolar-mode static induction transistors (BSIT), a new driving method, a zero-voltage-switched pulse-width-modulation technique, and a new litz wire with low AC resistance. It weighs only 16.5kg, has a volume of 26,000cm3, operates at 40kHz, and has a power conversion efficiency of about 95%. The power loss of this converter is 20% less than that of conventional natural-air-cooled DC-DC converters, and the power density is 3 times as high.