A noble blind equalization algorithm (BEA) using a single/multilevel modulus is proposed. According to the residual intersymbol interference (ISI) level of the equalizer output, the new algorithm adopts relevantly a single modulus or a multilevel modulus to form its cost function. Moreover, since the proposed approach separates complex two-dimensional signal into in-phase and quadrature components, and forms the error signals for each component, it has inherently the capability of phase recovery. Hence, it improves the performances of steady-state and recovers the phase rotation without any degradation of transient property. Simulation results confirm the effectiveness of the new approach.

The stable marriage problem is one of the basic problems proposed in 1962. In this paper, we consider a distributed stable marriage problem. This problem is applicable to cooperative works of autonomous robots in distributed environments. We show a Gale-Shapley based protocol to obtain stable matching and introduce autonomous mechanism for exchanging partners, called divorce process, in distributed environments. We report some interesting results of matching games by computer simulation.

Calculation Nv(x) of complex order v numerically, we must calculate Df{JN+ε(x)}. When Df{JN+ε(x)} is calculated by the recurrence method, this letter will analyze the error of Df{JN+ε(x)}, and will determine the optimum number of recurrences.

Event-related are the kind of signals that are time-related to a given event. In this work, we will study the effect of bias and overlapping noise on Fourier linear combiner (FLC)-based filters, and its implication on filtering event-related signals. We found that the bias alters the weights behaviour, and therefore the filter output, and we discuss solutions to the problem of spectral overlap.

A neural network approach called the "Gradual Neural Network (GNN)" for the time slot assignment problem in the TDM multicast switching system is presented in this paper. The goal of this NP-complete problem is to find an assignment of packet transmission requests into a minimum number of time slots. A packet can be transmitted from one source to several destinations simultaneously by its replication. A time slot represents a switching configuration of the system with unit time for each packet transmission through an I/O line. The GNN consists of the binary neural network and the gradual expansion scheme. The binary neural network satisfies the constraints imposed on the system by solving the motion equation, whereas the gradual expansion scheme minimizes the number of required time slots by gradually expanding activated neurons. The performance is evaluated through simulations in practical size systems, where the GNN finds far better solutions than the best existing altorithm.

This paper describes novel techniques for analyzing power MOSFETs. Since the gate width of power MOSFETs is much larger than that of power MESFETs or HJFETs, an appropriate device design to suppress matching circuit losses is needed. These losses and the intrinsic device characteristics are analyzed employing the proposed techniques, which are based on large-signal simulations. Also, new formulas describing the dependence of saturated output power on gate width are derived to perform loss-minimized design. These techniques are applied to the design of power MOSFETs for GSM cellular telephones. As a result, an output power of 35.5 dBm with a power-added efficiency of 55% and a power gain of 10.5 dB at 900 MHz have been achieved.

Today's enterprise information systems are modeled on the client/server paradigm over LANs interconnected by WANs, but it involves problems of network management costs and complicated management jobs. So efficient network management is strongly required for LANs interconnected by WANs. In this paper, we describe a hierarchical enterprise network management system for LANs interconnected by WANs, based upon analysis of LAN management operations. This network management system has a hierarchical model with three levels, i.e., center level, area level, and user-site level. We also describe how this system was implemented as a nation-wide corporate network with many LAN sites, emphasizing on its functional structure. This network's success has confirmed usefulness of the management system.

Cross talk in mode-division multiplexing system is studied. The mode patterns when the fiber is bent are observed in the experiment.

Neural networks can be used as associative memories which can learn problems of acquiring input-output relations presented by examples. The learning time problem addresses how long it takes for a neural network to learn a given problem by a learning algorithm. As a solvable model to this problem we analyze the learning dynamics of the linear associative memoty with the least-mean-square algorithm. Our result shows that the learning time τ of the linear associative memory diverges in τ (1-ρ)-2 as the memory rate ρ approaches 1. It also shows that the learning time exhibits the exponential dependence on ρ when ρ is small.

In many efforts to increase the efficiency of power amplifiers of mobile terminals, compensation of nonlinear distortion based on an adaptive predistortion method has performed an important role. In the course of basic evaluation of a method using a look-up table (LUT) and a method using an approximation for compensation of nonlinear distortion, a newly developed method using approximation and a ROM type LUT with a small-sized memory has been proposed to overcome barriers to practical application and disadvantages associated with the LUT method. Experimental trials of the proposed method were applied to narrow-band digital modulation systems. As a result, the proposed method was found to provide a satisfactory capability of compensating nonlinear distortion, with next adjacent channel interference of less than -55 dBc. The proposed method has advantages such as a small memory size and excellent RF performance, and is expected to occupy an important position in many adaptive predistortion methods.

This paper proposes the Snow Crystal method, which aims to present the hierarchies of a large-scale telecommunication network on one screen. This will improve the user interface of a network operation system for network operations and management. With the proposed presentation method, locations of nodes are automatically set based on the number of hierarchy levels and the number of nodes. The nodes in the same hierarchy level are located on the same circle at even intervals. The center of the circle that corresponds to the top hierarchy level is set at the center of the screen. The radius of the circle is determined by the number of nodes. The centers of circles that correspond to the second hierarchy levels belonging to the nodes of the top hierarchy level, are located on a larger circle with the same center point as the top level circle at even intervals. The centers of circles that correspond to the third hierarchy levels are located at even intervals on a circle with the same center point as the second level circle, which the third levels belong to. The nodes of the subsequent levels are located in the same way. The proposed presentation method is successfully applied to a large-scale telecommunication network. Moreover, the results of an operating experiment with the proposed method show its effectiveness for presenting hierarchies of large-scale telecommunication networks.

A GaAs SPDT switch IC operating at a low power supply voltage of 2.7 V has been developed for use in 1.9 GHz band personal handy phone system (PHS). In combination with MESFETs with low on-resistance and high breakdown voltage, the switch IC adopts parallel-LC resonant circuits and utilizes both stacked FETs and an additional shunt capacitor at the receiver side in order to realize low insertion loss, high isolation and low distortion characteristics. An insertion loss of 0.55 dB and an isolation of 35.8 dB were obtained at 1.9 GHz. The IC also achieved an output power of 25.0 dBm at 1 dB gain compression point, a second order distortion of -54.3 dBc and an adjacent channel leakage power of -66 dBc at 600 kHz apart from 1.9 GHz at 19 dBm output power.

In this paper, we present a new state space-based approach for the two-dimensional (2-D) frequency estimation problem which occurs in various areas of signal processing and communication problems. The proposed method begins with the construction of a state space model associated with the noiseless data which contains a summation of 2-D harmonics. Two auxiliary Hankel-block-Hankel-like matrices are then introduced and from which the two frequency components can be derived via matrix factorizations along with frequency shifting properties. Although the algorithm can render high resolution frequency estimates, it also calls for lots of computations. To alleviate the high computational overhead required, a highly parallelizable implementation of it via the principle subband component (PSC) of some appropriately chosen transforms have been addressed as well. Such a PSC-based transform domain implementation not only reduces the size of data needed to be processed, but it also suppresses the contaminated noise outside the subband of interest. To reduce the computational complexity induced in the transformation process, we also suggest that either the transform of the discrete Fourier transform (DFT) or the Haar wavelet transform (HWT) be employed. As a consequence, such an approach of implementation can achieve substantial computational savings; meanwhile, as demonstrated by the provided simulation results, it still retains roughly the same performance as that of the original algorithm.

Given the recent advances in telecommunication services, new service operations are needed that support not only existing network services, but also information and communication providing services, such as multimedia services. It is particularly important that service usage information should be gathered, processed, analyzed and presented properly for smooth service provisioning and business support. This paper defines a reference model for service usage information and an implementation model for establishing the functions needed to gather and process this information. The results of an service operation system as implemented in NTT multimedia service trials, currently underway in the city of Urayasu, are also described.

An analysis method is proposed for nonstationary waveforms. Modelling of a nonstationary waveform is first given in this paper. A waveform is represented by multiple oscillations. The instantaneous phase angle of each oscillation is written by three terms, predictive component, residual component, and initial phase constant. By this modelling, waveform analysis results in estimations of frequency, calculation of residual pbase in instantaneous phase angle. The Instantaneous Maximum Entropy Methods (IMEN) is utilized for frequency estimation. The residual phase angle is obtained by the Vandermonde matrix and the condition of continuity of phase angle among n-neighbourhood. Another analysis method is also proposed by the normalization of waveform parameters. The evaluation of the proposed method is done using artificially composed waveform signals. Novel and useful knowledge was provided by this analysis.

Our compact switching converter using a thin-film microtransformer mono-lithically integrated with rectifier diodes represents the first step in developing a monolithic micro-switching converter that can be integrated with semiconductor devices and magnetic components. This converter is a single-ended forward converter with resonant reset and operates successfully at 15 MHz. The maximum output power is 0.5 W.

Scattering of a plane electromagnetic wave by a conducting wedge will be discussed. The former solution can not be applicable to all the transition regions when its parameter is constant. This study shows a new solution which consists of only one expression applicable to the shadow region, the illuminated region and the transition regions, and which has no parameter.

Dynamic Term Rewriting Calculus is a new computation model proposed by the authors for the purpose of formal description and verification of algorithms treating Term Rewriting Systems. The computation of DTRC is basically term rewriting. The characteristic features of DTRC are dynamic change of rewriting rules during computation and hierarchical declaration of not only function symbols and variables but also rewriting rules. These features allow us to program metacomputation of TRSs in DTRC, that is , we can implement in DTRC in a natural way those algorithms which manipulate term rewriting systems as well as those procedures which verify such algorithms. In this paper, we give a formal description of DTRC. We then show some results on confluence property of DTRC.

In this paper, we propose an efficient task scheduling scheme, called CTS (Class-based Task Scheduling), to obtain high performance in terms of high system utilization and low waiting times for tasks. While a better submesh allocation scheme can improve system performance, an allocation policy alone cannot improve performance significantly. This is due to the fact that the FCFS task scheduling policy leads to large external fragmentation. The CTS strategy maintains four separate queues, one for each incoming task class. This avoids the blacking property incurred in the FCFS scheduling. To reduce the external fragmentation, a job tends to wait for an occupied submesh of the same size instead of using a new submesh in the CTS strategy. Simulation results indicate that the proposed scheduling strategy improves the performance compared to the FCFS scheduling policy by reducing the average waiting delay significantly.

Electric fishes generate an AC electric field around themselves by the electric organ in the tail. Spatial distortion of the field by nearby objects is detected by an electroreceptor array located an over the body surface to localize the object electrically when other senses such as vision and mechanosense are useless. Each fish has its own 'frequency band' for its electric organ discharges, and jamming of the electrolocation system occurs when two fish with similar discharge frequencies encounter. To avoid janmming, the fish shift their discharge frequencies in appropriate directions. A computational algorithm for this electrical behavior and its neuronal implementation by the brain have been discovered. The design features of the system, however, are rather complex for this simple behavior and cannot be readily explained by functional optimization processes during evolution. To gain insights into the origin of the design features, two independently evolved electric fish species which perform the same behavior are compared. Complex features of the neuronal computation may be explained by the evolutionary history of neuronal elements.