Low Power design has emerged as a both practically and theoretically attractive theme in modern LSI system design. This paper presents system level power optimization techniques. A brief survey of system level low power design approaches and several examples in detail are described. It reviews some techniques that have been proposed to overcome the power issue and gives guideline for prospective system level solutions.

We introduce a new wavelet image coding framework using context-based zerotree quantization, where an unique and efficient method for optimization of zerotree quantization is proposed. Because of the localization properties of wavelets, when a wavelet coefficient is to be quantized, the best quantizer is expected to be designed to match the statistics of the wavelet coefficients in its neighborhood, that is, the quantizer should be adaptive both in space and frequency domain. Previous image coders tended to design quantizers in a band or a class level, which limited their performances as it is difficult for the localization properties of wavelets to be exploited. Contrasting with previous coders, we propose to trace the localization properties with the combination of the tree-structured wavelet representations and adaptive models which are spatial-varying according to the local statistics. In the paper, we describe the proposed coding algorithm, where the spatial-varying models are estimated from the quantized causal neighborhoods and the zerotree pruning is based on the Lagrangian cost that can be evaluated from the statistics nearby the tree. In this way, optimization of zerotree quantization is no longer a joint optimization problem as in SFQ. Simulation results demonstrate that the coding performance is competitive, and sometimes is superior to the best results of zerotree-based coding reported in SFQ.

This paper proposes an Iterated Function System (IFS) which can reduce effects of quantization errors of the IFS parameters. The proposed method skips conventional analog-parameter search and directly selects optimum IFS parameters from pools of discrete IFS parameters. In conventional IFS-based image coding the IFS parameters are quantized after their analog optimum values are determined. The image reconstructed from the quantized parameters is degraded with errors that are traced back to quantization errors amplified in the iterated mappings. The effectiveness of this new realistic approach is demonstrated by simulation results over the conventional method.

The mathematical theory of bicomplex electromagnetic waves in two-dimensional scattering and diffraction problems is developed. The Vekua's integral expression for the two-dimensional fields valid only in the closed source-free region is generalized into the radiating field. The boundary-value problems for scattering and diffraction are formulated in the bicomplex space. The complex function of a single variable, which obeys the Cauchy-Riemann relations and thus expresses low-frequency aspects of the near field at a wedge of the scatterer, is connected with the radiating field by an integral operator having a suitable kernel. The behaviors of this complex function in the whole space are discussed together with those of the far-zone field or the amplitude of angular spectrum. The Hilbert's factorization scheme is used to find out a linear transformation from the far-zone field to the bicomplex-valued function of a single variable. This transformation is shown to be unique. The new integral expression for the field scattered by a thin metallic strip is also obtained.

Fuzzy rule-based edge detection using multiscale edge images is proposed. In this method, the edge image is obtained by fuzzy approximate reasoning from multiscale edge images which are obtained by derivative operators with various window sizes. The effect of utilizing multiscale edge images for edge detection is already known, but how to design the rules for deciding edges from multiscale edge images is not clarified yet. In this paper, the rules are represented in a fuzzy style, since edges are usually defined ambiguously, and the fuzzy rules are designed optimally by a training method. Here, the fuzzy approximate reasoning is expressed as a nonlinear function of the multiscale edge image data, and the nonlinear function is optimized so that the mean square error of the edge detection be the minimum. Computer simulations verify its high performance for actual images.

A quantization-based watermarking system for motion pictures is proposed. In particular, methods for improving the image quality of watermarked video, the watermarking data tolerance, and the accuracy of watermark data detection are described. A quantitative evaluation of the reliability of watermarked data, which has not generally been discussed up to now, is also performed.

Measurement of the viscosity of liquid using a piezoelectric disk is described. Experiments with a radial expansion mode of a piezoceramic disk were carried out for water-glycerin mixture samples. Resonant resistance has linearity to the square root of the product of density and viscosity of a liquid around 113 kHz.

In this paper, we describe our superconducting digital technology that uses Nb/AlOx/Nb Josephson junctions. Superconducting devices have intrinsically superior characteristics than those of semiconductor devices, and Nb/AlOx/Nb junctions have ideal current-voltage characteristics for digital applications. Superconducting devices that use Nb/AlOx/Nb junctions have being actively developed because of their high speed and low power characteristics. Presently, we can fabricate more than twenty thousand junctions on one chip. Using niobium technology, a superconducting 4-kbit RAM has been already successfully developed. We have demonstrated the operation of a network system with a superconducting network chip. Some problems, such as difficulty in high-speed testing, disturbance from trapped magnetic flux and so on, have been overcome by techniques such as a clock-driven testing method, moat structures and so on. The developed technologies, such as the fabrication technology, the design technology for moat structures and so on, must become the basic keys for the development of digital applications based on a single flux quantum device, which will be a promising component for ultra-high speed systems in the twenty-first century.

The noise level distribution owing to only a non-stationary working objective machine has been stochastically expressed by reflecting the temporal change of distribution parameters under a generalized regression model especially with aid of the vibration level observation. The proposed method has been applied to a noise evaluation of non-stationarily operated jigsaw.

This letter describes several techniques for optimizing software implementations of E2 on various platforms. We propose optimization techniques for each part of E2; a new inversion algorithm, efficient byte splitting and merging for BP-Function, and an efficient SPN (Substitution-Permutation Network) implementation for 32- or 64-bit processors. As a result, E2 achieves the encryption speeds of 100.5 kb/s, 68.3 Mb/s, 162.3 Mb/s, and 130.8 Mb/s for H8/300 (5 MHz), Pentium Pro (200 MHz), Pentium II (450 MHz), and 21164A (600 MHz).

In Asynchronous Transfer Mode (ATM) networks, congestion can be caused by unpredictable statistical fluctuations of traffic flows and fault conditions within the network. If congestion happens, then the network performance for the already established connection will decrease. ATM networks use the preventive congestion control mechanisms such as Usage Parameter Control (UPC) and Connection Admission Control (CAC) to avoid congested conditions. Knowing that many sources in ATM networks have variable traffic stream with different QoS characteristics, traffic management functions become necessary to control the traffic flows within the network. By using the signaling procedures at the call setup phase, the network and source reach an agreement for some traffic characteristic parameters. If the source violates the traffic parameters, then the probability of congestion increases. So the network must control the source traffic streams and detect well the violating cells. Therefore, fast detection of any violating source is one of the most important characteristics of a good traffic policer. In this paper we propose a fuzzy traffic policer with high ability in detection of violating sources. Our proposed fuzzy controller has two inputs, estimated passed mean cell rate and the current state of the counter. If the output of fuzzy controller is 1, then the input cell is detected as violating cell, otherwise it is a non-violating cell. Simulation results obtained from two traffic sources, show that the proposed traffic policer has better selectivity than the conventional leaky bucket. It is observed that our proposed traffic policer has better ability for mean cell rate control, peak cell rate control and burst duration control. Furthermore, it is observed that the proposed traffic policer outperforms the conventional leaky bucket specially when the dynamic behavior is considered.

It is the purpose of this paper to review the generation of quantized voltage steps in Josephson-junctions, and also the recent practical application of these precise measurements. A 10-V Josephson-junction-array-voltage standard system has been established with a Josephson-junction-array, a phase-locked millimeter wave, and a precise null-detection system. Based on these technologies, the AC Josephson effect has been applied to other precise measurements such as DC error voltage of a multi-integrating analog-to-digital converter and for a pulse-width-modulation type precise voltage calibrator.

A hierarchical structure of the statistical models involving the parametric, state space, generalized state space, and self-organizing state space models is explained. It is shown that by considering higher level modeling, it is possible to develop models quite freely and then to extract essential information from data which has been difficult to obtain due to the use of restricted models. It is also shown that by rising the level of the model, the model selection procedure which has been realized with human expertise can be performed automatically and thus the automatic processing of huge time series data becomes realistic. In other words, the hierarchical statistical modeling facilitates both automatic processing of massive time series data and a new method for knowledge discovery.

The abilities of fuzzy inference methods in modeling of complicated systems are implemented to electromagnetics for the first time. The very popular and well known monopole antenna is chosen as a general example and a fast, simple and accurate fuzzy model for its input impedance is made by introducing a new point of view to impedance basic parameters. It is established that a surprisingly little number of input data points is sufficient to make a full model and also the system behavior (dominant rules) are saved as simple membership functions. The validity of the derived rules is confirmed through applying them to the case of thin-angled monopole antenna and comparing the results with the measured. Finally using the spatial membership function context, input impedance of thick-angled monopole antenna is predicted and a novel view point to conventional electromagnetic parameters is discussed to generalize the modeling method.

We have developed a parameter optimization tool, Monte Carlo Josephson simulator (MJSIM), for rapid single flux quantum (RSFQ) digital circuits based on a Monte Carlo yield analysis. MJSIM can generate a number of net lists for the JSIM, where all parameter values are varied randomly according to the Gaussian distribution function, and calculate the circuit yields automatically. MJSIM can also produce an improved parameter set using the algorithm of the center-of-gravity method. In this algorithm, an improved parameter vector is derived by calculating the average of parameter vectors inside and outside the operating region. As a case study, we have optimized the circuit parameters of an RS flip-flop, and investigated the validity and efficiency of this optimization method by considering the convergency and initial condition dependence of the final results. We also proposed a method for accelerating the optimization speed by increasing 3σ spreads of the parameter distribution during the optimization.

Design of wireless communications systems with a transmission rate of 6 and 10 Mbit/s is presented for the 2.4 GHz Japanese ISM band, in which a spread spectrum technique named "CFO-SS (Carrier Frequency Offset-Spread Spectrum)" scheme is employed. In the CFO-SS system, a single PN code is commonly assigned to all the synchronized multiplexed carriers, and the frequency separation between carriers is determined by the transmission rate of each carrier. To realize the CFO-SS system, a timing acquisition and tracking scheme, an important part of the design, is presented first. Next, bit and packet error performance is investigated under severe multipath environments with/without a RAKE receiver. Degradation by channel bandwidth limitations, frequency inaccuracy of the hardware and co-channel interference (CCI) is also investigated by computer simulation. Simulation results presented confirmed sufficient performance of the CFO-SS system for wireless LAN systems using the 2.4 GHz ISM band.

This paper presents a new fuzzy dynamic output feedback controller design technique for the Takagi Sugeno (T-S) fuzzy model with unknown-but-bounded time-varying modeling error. It is shown that the quadratic stabilization problem of the T-S fuzzy modeled system can be converted into an H control problem of the scaled polytopic Linear Parameter Varying (LPV) system. Then, a controller satisfying a prescribed H performance is designed for the stabilization of the T-S fuzzy modeled system.

An accurate and efficient numerical solution is presented for a two-dimensional electromagnetic wave scattering from a multilayered resistive strip grating embedded in a dielectric slab. Both E- and H-waves are treated. The problem is formulated into a set of integral equations, which is solved by the moment method accompanied by a regularization procedure. The resultant set of linear algebraic equations has the form of the Fredholm second kind, and therefore yields stable and accurate numerical solutions. The power distribution is computed for several grating parameters. Attention is paid to seek a set of parameters that maximizes absorption in the strips. The low frequency approximate formulas are also derived. This analysis would be useful in designing electromagnetic wave absorbers.

In this paper, we present a new approach which is spanning tree-based genetic algorithm for solving a multi-objective transportation problem. The transportation problem as a special type of the network optimization problems has the special data structure in solution characterized as a transportation graph. In encoding transportation problem, we introduce one of node encodings based on a spanning tree which is adopted as it is capable of equally and uniquely representing all possible basic solutions. The crossover and mutation were designed based on this encoding. Also we designed the criterion that chromosome has always feasibility converted to a transportation tree. In the evolutionary process, the mixed strategy with (µ+λ)-selection and roulette wheel selection is used. Numerical experiments show the effectiveness and efficiency of the proposed algorithm.

Future cellular communication systems will be called upon to provide multimedia services (voice, data, and video) for various user platforms (pedestrians, cars, and trains) that have a variety of mobility characteristics. Knowledge of mobility characteristics is essential for planning, designing and operating communication networks. The position data of selected vehicles (taxis) have been measured by using the Global Positioning System at 1-s intervals. Those data are used for evaluating mobility characteristics, such as probabilistic distributions of speed, cell dwell time, and cell crossover rate of vehicles, assuming that cells are hypothetically laid over the loci of the vehicles. The cell dwell time of vehicles is found to follow a lognormal distribution, rather than a conventionally-presumed negative exponential distribution. When the holding time distribution and random origination of calls along the loci are assumed, the properties of the cell dwell time and the handoff rate of terminals communicating in the hypothetical cellular systems are also estimated from the measured data.