This paper proposes a gesture recognition method which uses higher order local autocorrelation (HLAC) features extracted from PARCOR images. To extract dominant information from a sequence of images, we apply linear prediction coding technique to the sequence of pixel intensities and PARCOR images are constructed from the PARCOR coefficients of the sequences of the pixel values. From the PARCOR images, HLAC features are extracted and the sequences of the features are used as the input vectors of the Hidden Markov Model (HMM) based recognizer. Since HLAC features are inherently shift-invariant and computationally inexpensive, the proposed method becomes robust to changes in the person's position and makes real-time gesture recognition possible. Experimental results of gesture recognition are shown to evaluate the performance of the proposed method.

This paper describes an Embedded DRAM Hybrid Macro, which supports various memory specifications. The eDRAM module generator with Hybrid Macro provides more than 120,000 eDRAM configurations. This eDRAM includes a new architecture called Auto Signal Management (ASM) architecture, which automatically adjusts the timing of the control signals for various eDRAM configurations, and reduces the design Turn Around Time. An Enhanced-on-chip Tester performs the maximum 512b I/O pass/fail simultaneous judgments and the real time repair analysis. The eDRAM testing time is reduced to about 1/64 of the time required using the conventional technique. A test chip is fabricated using a 0.18 µm 4-metal embedded DRAM technology, which utilizes the triple-well, dual-Tox, and Co salicide process technologies. This chip achieves a wide voltage range operation of 1.2 V at 100 MHz to 1.8 V at 200 MHz.

A new pilot-aided channel estimation technique is proposed and applied to wideband CDMA (WCDMA) systems. This technique is based on conventional pilot-aided decision directed (PADD) algorithms. In this letter, conventional PADD algorithms are studied extensively and a modified PADD algorithm is presented. The performance of the proposed algorithm is compared with that of conventional PADD algorithms through computer simulations in Rayleigh fading environments.

A parity check matrix for a binary linear code defines a bipartite graph (Tanner graph) which is isomorphic to a subgraph of a factor graph which explains a mechanism of the iterative decoding based on the sum-product algorithm. It is known that this decoding algorithm well approximates MAP decoding, but degradation of the approximation becomes serious when there exist cycles of short length, especially length 4, in Tanner graph. In this paper, based on the generating idempotents, we propose some methods to design parity check matrices for cyclic codes which define Tanner graphs with no cycles of length 4. We also show numerically error performance of cyclic codes by the iterative decoding implemented on factor graphs derived from the proposed parity check matrices.

This paper deals with contour extraction of fetus' head from echocardiogram and its application to diagnosis in obstetrics. Active contour model "SNAKES" is modified and used for contour extraction. After contour extraction we automatically obtained the biparietal diameter (BPD) and the occipitofrontal diameter (OFD) from the contour.

GPS receivers are susceptible to jamming by interference. This paper proposes a recurrent neural network (RNN) predictor for new application in GPS anti-jamming systems. Five types of narrowband jammers, i. e. AR process, continuous wave interference (CWI), multi-tone CWI, swept CWI, and pulsed CWI, are considered in order to emulate realistic conditions. As the observation noise of received signals is highly non-Gaussian, an RNN estimator with a nonlinear structure is employed to accurately predict the narrowband signals based on a real-time learning method. The node decoupled extended Kalman filter (NDEKF) algorithm is adopted to achieve better performance in terms of convergence rate and quality of solution while requiring less computation time and memory. We analyze the computational complexity and memory requirements of the NDEKF approach and compare them to the global extended Kalman filter (GEKF) training paradigm. Simulation results show that our proposed scheme achieves a superior performance to conventional linear/nonlinear predictors in terms of SNR improvement and mean squared prediction error (MSPE) while providing inherent protection against a broad class of interference environments.

In this paper, we present a novel beam-former capable of tracking a rapidly moving speaker in a very noisy environment. The localization algorithm extracts a set of candidate direction-of-arrival (DOA) for the signal sources using array signal processing methods in the frequency domain. A minimum variance (MV) beam-former identifies the speech signal DOA in the direction where the signal's spectrum entropy is minimized. A fine tuning process detects the MV direction which is closest to the initial estimation using a smaller analysis window. Extended experiments, carried out in the range of 20-0 dB SNR, show significant improvement in the recognition rate of a moving speaker especially in very low SNRs (from 11.11% to 43.79% at 0 dB SNR in anechoic environment and from 9.9% to 30.51% in reverberant environment).

A new multi-luminance-level subfield method is proposed to reduce the low gray-level contour of an alternate current plasma display panel (AC-PDP). The minimum or maximum luminance level per sustain-cycle can be altered by simultaneously applying the proper auxiliary short pulses. As a result, the multi-luminance levels per one or two sustain pulse pairs can be expressed by properly adjusting the auxiliary short pulses for the one or two sustain-cycle subfields, thereby suppressing a low gray-level contour of AC-PDP.

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.

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.

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.

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.

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.

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 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.

A novel postprocessing algorithm for reducing the blocking artifacts in block-based coded images is proposed using block classification and adaptive multi-layer perceptron (MLP). This algorithm is exploited the nonlinearity property of the neural network learning algorithm to reduce the blocking artifacts more accurately. In this algorithm, each block is classified into four classes; smooth, horizontal edge, vertical edge, and complex blocks, based on the characteristic of their discrete cosine transform (DCT) coefficients. Thereafter, according to the class information of the neighborhood block, adaptive neural network filters (NNF) are then applied to the horizontal and vertical block boundaries. That is, for each class a different two-layer NNF is used to remove the blocking artifacts. Experimental results show that the proposed algorithm produced better results than conventional algorithms both subjectively and objectively.

Intelligent paging uses the sequential paging technique with additional user information in order to reduce the paging delay cost and the paging load cost. Our proposed paging scheme uses distribution density information of users as required additional user information. This letter addresses an optimal paging sequence and introduces formulas to calculate the paging costs. These formulas are necessary to evaluate the performance of location management. The paging delay cost and the paging load cost for the proposed paging scheme and two other paging schemes are calculated and numerical analyses for these paging schemes are performed. Results show how the paging delay cost and the paging load cost vary as either the paging request arrival rates or the number of cells in an LA increases. The proposed paging scheme is more efficient in view of both the paging delay cost and the paging load cost.

This study is a detailed numerical investigation on the relations between the performance of the RZ format single-channel transmission, and the chromatic dispersion of transmission fiber and pre-compensation ratio. We observed the transition from the SPM dominant low dispersion region to the intra-channel nonlinearities dominant high dispersion region, and found that the EOP is very sensitive to the pre-compensation ratio when the dispersion assumes a intermediate value. Furthermore, by analyzing the optical power-dependence of the EOP and other nonlinear impairments, we found that the amplitude fluctuation resulting from IFWM is dominant in determining the EOP in the transmission systems employing highly dispersed pulses.

In this paper, a modified Gardner's timing-error estimation algorithm is proposed for space-time block coding (STBC) schemes. In STBC schemes, the symbol timing-error can be estimated for each received antenna. The proposed algorithm is the diversity combining of all symbol timing-error estimates using Gardner's algorithm with the assumptions of identical channel delay of each SISO sub-stream. Simulation results show the proposed algorithm improves the symbol timing-error estimation performance through diversity gains. Estimation of symbol timing-error in multiple-input and multiple-output (MIMO) antenna systems is an another suitable area of application.

We propose a simple technique for reducing the jitter of the output clock generated in the clock recovery circuit (CRC) for burst-mode data transmission. By using this technique, the proposed CRC based on the gated oscillator (GO) can recover the output clock with a low-jitter even when there are consecutive same data streams encountered in the system. The circuit is composed only of digital logic devices and can recover the input data errorless until 1,000 consecutive same data bits are incoming.