In this paper, a novel noise parameters extraction technique for microwave packaged BJT and FET is proposed. The noise parameters of packaged BJT and FET for the entire operating frequency band can be obtained from the four noise parameters measured at a single frequency or a few frequencies. The predicated results obtained with this method agree well with the measured data. As a result, the novel noise parameters extraction technique can be used to predict the noise with a minimum effort.

In this paper, we presented an analysis of single and coupled microstrip lines covered with protective dielectric film which is usually used in the microwave integrated circuits. The method employed in the characterization is called partial-boundary element method (p-BEM). The p-BEM provides an efficient means to the analysis of the structures with multilayered media or covered with protective dielectric film. The numerical results show that by changing the thickness of the protective dielectric films such as SiO2, Si and Polyimide covered on these lines on a GaAs substrate, the coupled microstrip lines vary within 10% on the characteristic impedance and within 25% on the effective dielectric constant for the odd mode of coupled microstrip line, respectively, in comparison with the structures without the protective dielectric film. In contrast, the single microstrip lines vary within 4% on the characteristic impedance and within 8% on the effective dielectric constant, respectively. The protective dielectric film affects the odd mode of the coupled lines more strongly than the even mode and the characteristics of the single microstrip lines.

This paper presents an improved neural network for channel assignment problems in cellular mobile communication systems in the new co-channel interference model. Sengoku et al. first proposed the neural network for the same problem, which can find solutions only in small size cellular systems with up to 40 cells in our simulations. For the practical use in the next generation's cellular systems, the performance of our improved neural network is verified by large size cellular systems with up to 500 cells. The newly defined energy function and the motion equation with two heuristics in our neural network achieve the goal of finding optimum or near-optimum solutions in a nearly constant time.

We have designed and implemented a simple yet powerful declarative synchronization mechanism for a paralle object-oriented computation model. The mechanism allows the user to control multiple message reception, specify the order of message reception, lock an invocation, and specify relations as invocation constraints. It has been included in a parallel object-oriented language, called A-NETL. The compiler and operating system have been developed on a total architecture, A-NET (Actors NETwork). The experimental results show that (i) the mechanism allows the user to model asynchronous events naturally, without losing the integrity of described programs; (ii) the replacement of the mechanism with the user's code requires tedious descriptions, but gains little performance enhancement, and certainly loses program readability and integrity; (iii) the mechanism allows the user to shift synchronous programs to asynchronous ones, with a scalable reduction of execution times: an average 20.6% for 6 to 17 objects and 46.1% for 65 objects. These prove the effectiveness of the proposed synchronization mechanism.

In this paper, we propose two parallel processing methods for multidimensional (MD) sampling lattice alteration. The use of our proposed methods enables us to alter the sampling lattice of a given MD signal sequence in parallel without any redundancy caused by up- and down-sampling, even if the alteration is rational and non-separable. Our proposed methods are provided by extending two conventional block processing techniques for FIR filtering: the overlap-add method and the overlap-save method. In these proposed methods, firstly a given signal sequence is segmented into some blocks, secondly sampling lattice alteration is implemented for each block data individually, and finally the results are fitted together to obtain the output sequence which is identical to the sequence obtained from the direct sampling lattice alteration. Besides, we provide their efficient implementation: the DFT-domain approach, and give some comments on the computational complexity in order to show the effectiveness of our proposed methods.

To support high bit rate and high quality indoor radio communication systems, we have to solve intersymbol interference (ISI) problem caused by frequency-selective fading. Recently multi-carrier modulation technique is considered to be one of the effective methods for this problem. In this paper we propose Partial Frequency ARQ (Automatic Repeat reQuest) system which can achieve effective ARQ scheme for multi-carrier packet communication. This system operates partial retransmission of erroneous power faded packets, and it is superior to the traditional ARQ systems. Furthermore two different protocols are examined for this system: Static Carrier Assignment (SCA) and Dynamic Carrier Assignment (DCA). By computer simulation we found that DCA method can achieve better performance than SCA in terms of both throughput and packet transmission delay.

The electroretinogram (ERG) is used to diagnose many kinds of eye diseases. Our final purpose in this paper is a detection of diabetic retinopathy by using only ERG. In this paper, we describe a method to examine whether presented ERG data belong to a group of diabetic retinopathy. The ERG mainly consists of the a-wave, the b-wave and the oscillatory potential (op-wave). It was known that the op-wave varies as progress of retinopathy. Thus, we use the latency, the amplitude and the peak frequency of the op-wave. First, we study these features of sample ERG data, statistically. It was clarified that some of these characteristics are significantly different between a normal group and a group of diabetic retinopathy. By using some of these characteristics, we classify unknown ERG data on the basis of the Mahalanobis' generalized distance or the linear discriminant function. The highest accuracy of this method for the unknown data is about 92.73%.

This paper presents a simple and efficient method for estimation of parameters useful for textured image analysis. On the basia of a 2-D Wold-like decomposition of homogenenous random fields, the texture field can be decomposed into a sum of two mutually orthogonal components: a deterministic component and an indeterministic component. The spectral density function (SDF) of the former is a sum of 1-D or 2-D delta functions. The 2-D autocorrelation function (ACF) of the latter is fitted to the assumed anisotropic ACF that has an elliptical contour. The parameters representing the ellipse and those representing the delta functions can be used to detect rotation angles and scaling factors of test textures. Specially, rotation and scaling invariant parameters, which are applicable to the classification of rotated and scaled textured images, can be estimated by combining these parameters. That is, a test texture can be correctly classified even if it is rotated and scaled. Several computer experiments on natural textures show the effectiveness of this method.

Ever increasing demand for higher bandwidth memories, which is fueled by multimedia and 3D graphics, seems to be somewhat satisfied with various emerging memory solutions. This paper gives a review of these emerging DRAM architectures and a performance comparison based on a condition to let the readers have some perspectives of the future and optimized graphics systems.

This paper describes the new α-particle induced soft error mechanism, the Minority Carrier Outflow (MCO) effect, which may seriously affect the reliability of the scaled DRAMs with three dimensional capacitors. The MCO chargge increases as the device size miniaturizes because of the three dimensional capacitor effect as below. As the device scales down, the storage node volume decreases which results in the higher minority carrier density in the storage node and larger outflow charge. Also as the device plan view miniaturizes, the stack capacitor height or trench depth does not scales down or even increases to keep the storage node capacitance, therefore the initially generated minority carrier becomes larger. A simple analytical MCO model is introduced to evaluate the MCO effect quantitatively. The model agrees well with the three dimensional device simulation. The MCO model predicts that the life time of the minority carrier in the storage node strongly affects the MCO charge, however, even when the life time is as small as the order of 100 ps, the MCO effect can be the major soft error mechanism.

The applicability of Dynamic Channel Assignment methods to a Reuse Partitioning system in cellular radio systems is investigated in this paper. The investigations indicate that such a system has a tendency to increase the difference between blocking probability for the partitioning two coverage areas in comparison with the conventional Reuse Partitioning system employing Fixed Channel Assignment method. Two schemes using new Channel Rearrangement algorithms are also proposed in order to alleviate the difference as a disadvantage which gives unequal service to the system. The simulation results show that the proposed schemes are able to reduce the difference significantly while increasing the carried traffic by 10% as compared with the conventional system.

In this paper, we develop parallel scrambling techniques for the distributed sample scrambling (DSS), which are directly applicable to the bit- and multibit-interleaved multiplexing environments. We first consider how to realize PSRGs, parallel samplings and parallel corrections for the multibit-parallel DSS (MPDSS), which are the fundamental problems in realizing the MPDSS scramblers and descramblers. The results are summarized in three sets of theorems, and a corollary is attached to each theorem to specifically handle the case of the parallel DSS (PDSS). The theorems and corollaries are supported by examples that demonstrate the relevant MPDSS scramblers and descramblers.

The firing squad synchronization problem is considered for defective cellular automata. A lower bound of time tf for the problem is derived. The state complexity to solve the problem is investigated and it is shown that the state set has to be arbitrary large to obtain solutions of time complexity (n). For memory-augmented defective cellular automata a tf-time solution is given.

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.

Although consistent learning is sufficient for PAC-learning, it has not been found what strategy makes learning more efficient, especially on the sample complexity, i.e., the number of examples required. For the first step towards this problem, classes that have consistent learning algorithms with one-sided error are considered. A combinatorial quantity called maximal particle sets is introduced, and an upper bound of the sample complexity of consistent learning with one-sided error is obtained in terms of maximal particle sets. For the class of n-dimensional axis-parallel rectangles, one of those classes that are consistently learnable with one-sided error, the cardinality of the maximal particle set is estimated and O(d/ε1/ε log 1/δ) upper bound of the learning algorithm for the class is obtained. This bound improves the bounds due to Blumer et al. and meets the lower bound within a constant factor.

Motion estimation is a major part of the video coding, which traces the motion of moving objects in video sequences. Among various motion estimation algorithms, the Hierarchical Block-Matching Algorithm (HBMA) that is a multilayered motion estimation algorithm is attractive in motion-compensated interpolation when accurate motion estimation is required. However, parallel processing of HBMA is necessary since the high computational complexity of HBMA prevents it from operating in real-time. Further, the repeated updates of vectors naturally lead to pipelined processing. In this paper, we present a pipelined architecture for HBMA. We investigate the data dependency of HBMA and the requirements of the pipeline to operate synchronously. Each pipeline stage of the proposed architecture consists of a systolic array for the block-matching algorithm, a bilinear interpolator, and a latch mechanism. The latch mechanism mainly resolves the data dependency and arranges the data flow in a synchronous way. The proposed architecture achieves nearly linear speedup without additional hardware cost over a non-pipelined one. It requires the clock of 2.70 ns to process a large size of frame (e.q. HDTV) in real-time, which is about to be available under the current VLSI technology.

This letter presents new estimation algorithm of ARMAX systems which do not always satisfy the strictly positive real (SPR) condition. We show how estimated parameters can converge to their true values based on the overparameterized system. Finally, the results of computer simulation are presented to illustrate the effectiveness of the proposed method.

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.

The Manchester Dataflow Machine (MDFM) works with tasks of size equal to one single instruction. This fine granularity aims at exploring all parallelism at the instruction level. However, this project decision increases the instruction communication cost, which ends up to jam the interconnection network and reduces the system performance. One way to skirt this problem is to adopt variable size tasks instead of working with such small task size. In this paper, in order to study whether or not the usage of such variable size tasks in the MDFM architecture contributes to the improvement of the performance, some simulations by toy programs take place. In the simulation, variable size tasks are realized by packing the sequential instruction stretches into one task. To manage this packing, the Sequential Block (SB) technique is developed. The simulation of those packed and unpacked programs give an outline of advantages and disadvantages of working with variable size tasks, and how the SB technique should be implemented in the system.

A graph G is said to be universal for a family F of graphs if G contains every graph in F as a subgraph. A minimum universal graph for F is a universal graph for F with the minimum number of edges. This paper considers a minimum universal graph for the family Fkn of graphs on n vertices with path-width at most k. We first show that the number of edges in a universal graph Fkn is at least Ω(kn log(n/k)). Next, we construct a universal graph for Fkn with O(kn log(n/k)) edges, and show that the number of edges in a minimum universal graph for Fkn is Θ(kn log(n/k)) .