The problem of optimal placement of pilot symbols is considered for single carrier packet-based transmission over time varying channels. Both flat and frequency-selective fading channels are considered, and the time variation of the channel is modeled by Gauss-Markov process. The semi-blind linear minimum mean-square error (LMMSE) channel estimation is used. Two different performance criteria, namely the maximum mean square error (MSE) of the channel tap state over a packet and the cumulative channel MSE over a packet, are used to compare different placement schemes. The pilot symbols are assumed to be placed in clusters of length (2L+1) where L is the channel order, and only one non-zero training symbols is placed at the center of each cluster. It is shown that, at high SNR, either performance metric is minimized by distributing the pilot clusters throughout the packet periodically. It is shown that at low SNR, the placement is in fact not optimal. Finally, the performance under the periodic placement is compared with that obtained with superimposed pilots.

This paper presents novel techniques for blind separation and blind extraction of instantaneously mixed binary sources, which are suitable for the case with less sensors than sources. First, a solvability analysis is presented for a general case. Necessary and sufficient conditions for recoverability of all or some part of sources are derived. A new deterministic blind separation algorithm is then proposed to estimate the mixing matrix and separate all sources efficiently in the noise-free or low noise level case. Next, using the Maximum Likelihood (ML) approach for robust estimation of centers of clusters, we have extended the algorithm for high additive noise case. Moreover, a new sequential blind extraction algorithm has been developed, which enables us not only to extract the potentially separable sources but also estimate their number. The sources can be extracted in a specific order according to their dominance (strength) in the mixtures. At last, simulation results are presented to illustrate the validity and high performance of the algorithms.

In this paper, we present a novel portrait impression estimation method using nine pairs of semantic impression words: bitter-majestic, clear-pure, elegant-mysterious, gorgeous-mature, modern-intellectual, natural-mild, sporty-agile, sweet-sunny, and vivid-dynamic. In the first part of the study, we analyzed the relationship between the facial features in deformed portraits and the nine semantic impression word pairs over a large dataset, which we collected by a crowdsourcing process. In the second part, we leveraged the knowledge from the results of the analysis to develop a ranking network trained on the collected data and designed to estimate the semantic impression associated with a portrait. Our network demonstrated superior performance in impression estimation compared with current state-of-the-art methods.

This paper discusses a nonlinear function for independent component analysis to process complex-valued signals in frequency-domain blind source separation. Conventionally, nonlinear functions based on the Cartesian coordinates are widely used. However, such functions have a convergence problem. In this paper, we propose a more appropriate nonlinear function that is based on the polar coordinates of a complex number. In addition, we show that the difference between the two types of functions arises from the assumed densities of independent components. Our discussion is supported by several experimental results for separating speech signals, which show that the polar type nonlinear functions behave better than the Cartesian type.

This paper considers a link of two problems; multichannel blind deconvolution and multichannel blind identification of linear time-invariant dynamic systems. To solve these problems, cumulant maximization has been proposed for blind deconvolution, while cumulant matching has been utilized for blind identification. They have been independently developed. In this paper, a cumulant maximization criterion for multichannel blind deconvolution is shown to be equivalent to a least-squares cumulant matching criterion after multichannel prewhitening of channel outputs. This equivalence provides us with a new link between a cumulant maximization criterion for blind deconvolution and a cumulant matching criterion for blind identification.

This paper proposes two techniques for improving the accuracy of gate-level power analysis for system-on-a-chip (SoC). (1) Creation of custom wire load models for clock nets. (2) Use of layout information (actual net capacitance and input signal transition time). The analysis time is reduced to less than one three-hundredth of the transistor-level power analysis time. Error is within 5% against a real chip, (the same level as that of the transistor-level power analysis), if technique (2) is used, and within 15% if technique (1) is used.

In certain computer and communication systems, the significant number of byte errors are not hard errors, but a few transient bit errors confined to byte regions. This kind of byte errors are called spotty byte errors, meaning, not all, but only 2 or 3 random bits, are corrupted in a byte. Especially, the codewords of memory systems which use recent high density wide I/O data semiconductor DRAM chips are prone to this kind of spotty byte errors. This is because, the presence of strong electromagnetic waves in the environment or the bombardment of an energetic particle on a DRAM chip is highly likely to upset more than just one bit stored in that chip. Under this situation, codes capable of correcting single spotty byte errors are suitable for application in semiconductor memory systems. This paper defines a spotty byte error as a random t-bit error confined to a b-bit byte and proposes a class of codes called Single t/b-error Correcting (St/bEC) codes which are capable of correcting single spotty byte errors occurring in computer and communication systems. For the case where the chip data output is 16 bits, i.e., b=16, the S3/16EC code proposed in this paper requires only 16 check bits, that is, only one chip is required for check bits at practical information lengths such as 64, 128 and 256 bits. Furthermore, this S3/16EC code is capable of detecting more than 95% of all single 16-bit byte errors at information length 64 bits.

The goal of the maximum cut problem is to partition the vertex set of an undirected graph into two parts in order to maximize the cardinality of the set of edges cut by the partition. The maximum cut problem has many important applications including the design of VLSI circuits and communication networks. Moreover, many optimization problems can be formulated in terms of finding the maximum cut in a network or a graph. In this paper, we propose an improved Hopfield neural network algorithm for efficiently solving the maximum cut problem. A large number of instances have been simulated. The simulation results show that the proposed algorithm is much better than previous works for solving the maximum cut problem in terms of the computation time and the solution quality.

In a previous study about a combinatorial optimization problem solver using neural networks, since the Hopfield method, convergence to the optimum solution sooner and with more certainty is regarded as important. Namely, only static states are considered as the information. However, from a biological point of view, dynamical systems have attracted attention recently. Therefore, we propose a "dynamical" combinatorial optimization problem solver using hysteresis neural networks. In this paper, the proposed system is evaluated by the N-Queen problem.

The main purpose of our method is to obtain realistic worst-case delay in statistical timing analyses. This paper proposes a method of statistical delay calculation based on measured intra-chip and inter-chip variabilities. We present a modeling and extracting method of transistor characteristics for the intra-chip variability and the inter-chip variability. In the modeling of the intra-chip variability, it is important to consider a gate-size dependence by which the amount of intra-chip variation is affected. This effect is not captured in a statistical delay analysis reported so far. Our method proposes a method for modeling of the device variability and statistical delay calculation with consideration of the size dependence, and uses a response surface method (RSM) to calculate a delay variation with low processing cost. We evaluate the accuracy of our method, and we show some experimental results the variation of a circuit delay characterized by the measured variances of transistor currents.

In this paper, we propose a function that provides scalability of image quality on the basis of regions of interest for JPEG2000 coding. Functions of this type are useful in the progressive transmission of images, where the aim is to more quickly decode regions of interest than backgrounds. The conventional methods of progressive transmission have mainly been based on SNR scalability or on resolution scalability. With these conventional functions, it is impossible to achieve region-based scalability in the progressive transmission of images. The proposed methods use the ROI and SNR layer structures of JPEG2000, so the methods are suitable for the region-progressive transmission of JPEG2000 images.

A method of error concealment for JPEG2000 images is proposed in this paper. The proposed method uses the layer structure that is a feature of the JPEG2000. The most significant layer is hidden in the lowest layer of the JPEG2000 bit stream, and this embedded layer is used for error concealment. The most significant layer is duplicated because JPEG2000 uses bit-plane coding. In this coding, when the upper layers are affected by errors, the coefficients of the lower layers become meaningless. A bit stream encoded using the proposed method has the same data structure as a standard JPEG2000. Therefore, it can be decoded by a standard decoder. Our simulation results demonstrated the effectiveness of the proposed method.

Several lifting implementation techniques for invertible deniterlacing are proposed in this paper. Firstly, the invertible deinterlacing is reviewed, and an efficient implementation is presented. Next, two deinterlacer-embedded lifting architectures of discrete wavelet transforms (DWT) is proposed. Performances are compared among several architectures of deinterlacing with DWT. The performance evaluation includes dual-multiplier and single-multiplier architectures. The number of equivalent gates shows that the deinterlacing-embedded architectures require less resources than the separate implementaion. Our experimental evaluation of the dual-multiplier architecture results in 0.8% increase in the gate count, whereas the separate implementation of deinterlacing and DWT requires 6.1% increase from the normal DWT architecture. For the proposed single-multiplier architecture, the gate count is shown to result in 4.5% increase, while the separate counterpart yields 10.7% increase.

This paper presents the design considerations for a digital dental X-ray system with a commercial CCD sensor. Especially the system should be able to work with several X-ray machines even with them for the classical film. The hardware-software co-design methodology is employed to optimize the system. The full digital implementation is assumed for the reliability of the system. The considered functions cover the pre-processing such as the exposure detection, clamping and the dark level correction and the post-processing such as gray level compensation. It is analyzed with some other constraints in order to make the final partition. The entire system based on the partition will be described.

This paper presents an observer design methodology for a special class of MIMO nonlinear systems. First, we characterize the class of MIMO nonlinear systems that consists of the linear observable part and the nonlinear part with a block triangular structure. Also, the similarity transformation that plays an important role in proving the convergence of the proposed observer is generalized to MIMO systems. Since the gain of the proposed observer minimizes a nonlinear part of the system to suppress for the stability of the error dynamics, it improves the transient performance of the high gain observer. Moreover, by using the generalized similarity transformation, it is shown that under some observability and boundedness conditions, the proposed observer guarantees the global exponential convergence to zero of the estimation error. Finally, the simulation results for induction motor are included to illustrate the validity of our design scheme.

The paper is concerned with an identification-based predistortion scheme for compensating nonlinearity of high power amplifiers (HPA). The identification algorithms for the Wiener-Hammerstein nonlinear model are developed in the frequency domain. By approximately modeling the nonlinear distortion part in HPA by polynomial or spline functions, and introducing linear distortion parts in the input and output of the nonlinear element, the iterative identification schemes are proposed to estimate all the uncertain parameters and to construct an inverse system for the predistortion.

The authors have been investigating degradation process of Au plated slip ring and Ag-Pd-Cu brush system. In almost all cases the lifetime of the sliding system ends, when Au plating layer is worn out, the ring surface is oxidized to be black in color and contact resistance becomes very high. Further, the lifetime is very short without lubricant. So, the lubricant is very effective to make the lifetime longer. However, even with lubricant the lifetime is varied from about 1000 hours to almost 7000 hours in the past experiments. It is an important issue how the lubricant works on the lifetime of the system. In this paper the effect of lubricant on the degradation process of contact resistance is focused on. In the past tests the lubricant is supplied only once before the test. In this test the lubricant is regularly supplied almost every 900 operation hours. Consequently, the operation more than 8000 hours is realized, which is the longest among tests so far. In addition the contact voltage drop increase gradually until 2600 hours and after that it stays almost constant around 70 mV. According to the Element Analysis after the test the Ni base plating layer is totally exposed in many tracks. It means that the Au plating layer is gradually worn out probably at the stage of increasing voltage drop. In the previous tests the lifetime ended even when the Ni plating layer remained. So, the reason of long operation in this test is guessed to be that the lubricant not only decreases wear of ring and brush, but also suppresses oxidation of the Ni layer.

A heterogeneous parallel computing environment consisting of different types of workstations and communication links plays an important role in parallel computing. In many applications on the system, collective communication operations are commonly used as communication primitives. Thus, design of the efficient collective communication operations is the key to achieve high-performance parallel computing. But the heterogeneity of the system complicates the design. In this paper, we consider design of an efficient gather operation, one of the most important collective operations. We show that an optimal gather schedule is found in O(n2k-1) time for the heterogeneous parallel computing environment with n processors of k distinct types, and that a nearly-optimal schedule is found in O(n) time if k=2.

This paper proposes a gradient ascent learning algorithm for the elastic net approach to the Traveling Salesman Problem (TSP). The learning model has two phases: an elastic net phase, and a gradient ascent phase. The elastic net phase is equivalent to gradient descent of an energy function, and leads to a local minimum of energy that represents a good solution to the problem. Once the elastic net gets stuck in local minima, the gradient ascent phase attempts to fill up the valley by modifying parameters in a gradient ascent direction of the energy function. Thus, these two phases are iterated until the elastic net gets out of local minima. We test the algorithm on many randomly generated travel salesman problems up to 100 cities. For all problems, the systems are shown to be capable of escaping from the elastic net local minima and generating shorter tour than the original elastic net.

We have classified parenchymal echo patterns of cirrhotic liver into four types, according to the size of hypo echoic nodular lesions. The NN (neural network) technique has been applied to the characterization of hepatic parenchymal diseases in ultrasonic B-scan texture. We employed a multilayer feedforward NN utilizing the back-propagation algorithm. We extracted 1616 pixels in the two-dimensional regions. However, when a large area is used, input data becomes large and much time is needed for diagnosis. In this report, we used DCT (discrete cosine transform) for the feature extraction of input data, and compression. As a result, DCT was found to be suitable for compressing ultrasonographic images.