The Liquid-crystal display (LCD) overdrive technique has been utilized to reduce motion blur on a display via a reduction in the response time. However, to measure the variation of the pixel amplitudes, it is necessary to store the previous frame using a large frame memory. To downscale the frame memory, block truncation coding (BTC) is commonly employed due to the simplicity of its implementation, even if some visual artifacts may occur for image blocks with high frequency components. In this paper, we present a multimode-multilevel BTC (MBTC) technique that improves performance while maintaining simplicity. To improve the visual quality, we uniquely determine the quantization level and coding mode of each block according to the distribution of the luminance and chrominance amplitudes. For a compression ratio of 6:1, the proposed method demonstrates higher coding efficiency and overdrive performance by up to 3.81 dB in the PSNR compared to other methods.

This paper proposes a video-quality estimation method based on a reduced-reference model for realtime quality monitoring in video streaming services. The proposed method chooses representative-luminance values for individual original-video frames at a server side and transmits those values, along with the pixel-position information of the representative-luminance values in each frame. On the basis of this information, peak signal-to-noise ratio (PSNR) values at client sides can be estimated. This enables realtime monitoring of video-quality degradation by transmission errors. Experimental results show that accurate PSNR estimation can be achieved with additional information at a low bit rate. For SDTV video sequences which are encoded at 1 to 5 Mbps, accurate PSNR estimation (correlation coefficient of 0.92 to 0.95) is achieved with small amount of additional information of 10 to 50 kbps. This enables accurate realtime quality monitoring in video streaming services without average video-quality degradation.

A simplified algorithm for check node processing of extended min-sum (EMS) q-ary LDPC decoders is presented in this letter. Compared with the bubble check algorithm, the so-called dynamic bubble-check (DBC) algorithm aims to further reduce the computational complexity for the elementary check node (ECN) processing. By introducing two flag vectors in ECN processing, The DBC algorithm can use the minimum number of comparisons at each step. Simulation results show that, DBC algorithm uses significantly fewer comparison operations than the bubble check algorithm, and presents no performance loss compared with standard EMS algorithm on AWGN channels.

OFDM/offset-QAM (OFDM/OQAM) has been proven to be a promising multi-carrier transmission technique. However, carrier frequency offset (CFO) can lead to severe inter-carrier interference (ICI) and performance degradation. Meanwhile, channel estimation is also an important issue because of the intrinsic characteristics of OFDM/OQAM. In this paper, a novel pilot structure and a frequency-domain cross-correlation algorithm are proposed for the joint CFO and channel estimation. Analysis and simulation results validate the effectiveness of the proposed pilot structure and estimation algorithm.

This letter proposes an automatic IQ imbalance compensation technique for quadrature modulators by means of spectrum measurement of RF signal using a spectrum analyzer. The analyzer feeds back only magnitude information of the frequency spectrum of the signal. To realize IQ imbalance compensation, the conventional method of steepest descent is modified; the descent direction is empirically determined and a variable step-size is introduced for accelerating convergence. The experimental results for a four-channel transmitter operating at 11 GHz are presented for verification.

The quasi-ARX neurofuzzy (Q-ARX-NF) model has shown great approximation ability and usefulness in nonlinear system identification and control. It owns an ARX-like linear structure, and the coefficients are expressed by an incorporated neurofuzzy (InNF) network. However, the Q-ARX-NF model suffers from curse-of-dimensionality problem, because the number of fuzzy rules in the InNF network increases exponentially with input space dimension. It may result in high computational complexity and over-fitting. In this paper, the curse-of-dimensionality is solved in two ways. Firstly, a support vector regression (SVR) based approach is used to reduce computational complexity by a dual form of quadratic programming (QP) optimization, where the solution is independent of input dimensions. Secondly, genetic algorithm (GA) based input selection is applied with a novel fitness evaluation function, and a parsimonious model structure is generated with only important inputs for the InNF network. Mathematical and real system simulations are carried out to demonstrate the effectiveness of the proposed method.

In this paper, we derive a simple formula to generate a wide-sense systematic generator matrix(we call it quasi-systematic) B for a Reed-Solomon code. This formula can be utilized to construct an efficient interpolation based erasure-only decoder with time complexity O(n2) and space complexity O(n). Specifically, the decoding algorithm requires 3kr + r2 - 2r field additions, kr + r2 + r field negations, 2kr + r2 - r + k field multiplications and kr + r field inversions. Compared to another interpolation based erasure-only decoding algorithm derived by D.J.J. Versfeld et al., our algorithm is much more efficient for high-rate Reed-Solomon codes.

We propose an iterative frequency estimation method for accuracy improvement of discrete Fourier transform (DFT) phase-based methods. It iterates frequency estimation and phase calculation based on the DFT phase-based methods, which maximizes the signal-to-noise floor ratio at the frequency estimation position. We apply it to three methods, the phase difference estimation, the derivative estimation, and the arctan estimation, which are known to be among the best DFT phase-based methods. Experimental results show that the proposed method shows meaningful reductions of the frequency estimation error compared to the conventional methods especially at low signal-to-noise ratio.

This letter proposes two efficient schemes for the joint estimation of symbol timing offset (STO) and carrier frequency offset (CFO) in orthogonal frequency division multiplexing (OFDM) based IEEE 802.16e systems. Avoiding the effects of inter symbol interference (ISI) over delay spread by the multipath fading channel is a primary purpose in the letter. To do this, the ISI-corrupted CP is excluded when a correlation function is devised for both schemes, achieving the improved performance. To demonstrate the efficiency of the proposed methods, the performance is compared with the conventional method and is evaluated by the mean square error (MSE), acquisition range of CFO, and complexity comparison.

Wireless broadcasting of heterogeneous XML data has become popular in many applications, where energy-efficient processing of user queries at the mobile client is a critical issue. This paper proposes a new index structure for wireless stream of heterogeneous XML data to enhance tuning time performance in processing path queries on the stream. The index called PrefixSummary stores for each location path in the XML data the address of a bucket in the stream which contains an XML node satisfying the location path and appearing first in the stream. We present algorithms to generate broadcast stream with the proposed index and to process a path query on the stream efficiently by exploiting the index. We also suggest a replication scheme of PrefixSummary within a broadcast cycle to reduce latency in query processing. By analysis and experiment we show the proposed PrefixSummary approach can reduce tuning time for processing path queries significantly while it can also achieve reasonable access time performance by means of replication of the index over the broadcast stream.

This paper proposes a new biquad structure based on a flipped voltage follower (FVF) for low-power and wide-bandwidth (BW) low pass filter. The proposed biquad structure consists of an FVF and a source follower (SF) for complex pole pair generation and zero cancellation. The presented design provides good linearity at low power consumption, owing to the voltage follower structures. A power/BW ratio (PBWR) is suggested as a performance metric to compare power efficiency to bandwidth, and the proposed biquad structure shows excellent PBWR, especially for low quality factor (Q) design. As a prototype, a fourth order Bessel filter was fabricated in 0.18 µm CMOS technology. The measured BW, power consumption, IIP3, and FoM are 120 MHz, 180 µW, 15 dBm, and 0.34 fJ, respectively.

We recently determined the values of intrinsic spin-orbit (SO) parameters for In0.52Al0.48As/In0.53Ga0.47As(10 nm)/In0.52Al0.48As (InGaAs/InAlAs) quantum wells (QW), lattice-matched to (001) InP, from the weak localization/antilocalization analysis of the low-temperature magneto-conductivity measurements [1]. We have then studied the subband energy spectra for the InGaAs/InAlAs double QW system from beatings in the Shubnikov de Haas (SdH) oscillations. The basic properties obtained here for the double QW system provides useful information for realizing nonmagnetic spin-filter devices based on the spin-orbit interaction [2].

This paper presents our recent work in regard to building Large Vocabulary Continuous Speech Recognition (LVCSR) systems for the Thai, Indonesian, and Chinese languages. For Thai, since there is no word boundary in the written form, we have proposed a new method for automatically creating word-like units from a text corpus, and applied topic and speaking style adaptation to the language model to recognize spoken-style utterances. For Indonesian, we have applied proper noun-specific adaptation to acoustic modeling, and rule-based English-to-Indonesian phoneme mapping to solve the problem of large variation in proper noun and English word pronunciation in a spoken-query information retrieval system. In spoken Chinese, long organization names are frequently abbreviated, and abbreviated utterances cannot be recognized if the abbreviations are not included in the dictionary. We have proposed a new method for automatically generating Chinese abbreviations, and by expanding the vocabulary using the generated abbreviations, we have significantly improved the performance of spoken query-based search.

In the near future, decentralized network systems consisting of a huge number of sensor nodes are expected to play an important role. In such a network, each node should control itself by means of a local interaction algorithm. Although such local interaction algorithms improve system reliability, how to design a local interaction algorithm has become an issue. In this paper, we describe a local interaction algorithm in a partial differential equation (or PDE) and propose a new design method whereby a PDE is derived from the solution we desire. The solution is considered as a pattern of nodes' control values over the network each of which is used to control the node's behavior. As a result, nodes collectively provide network functions such as clustering, collision and congestion avoidance. In this paper, we focus on a periodic pattern comprising sinusoidal waves and derive the PDE whose solution exhibits such a pattern by exploiting the Fourier method.

Clustering technology is very important in ad hoc networks and sensor networks from the view point of reducing the traffic load and energy consumption. In this paper, we propose a new structure formation mechanism as a tool for clustering. It meets the key clustering requirements including the use of an autonomous decentralized algorithm and a consideration of the situation of individual nodes. The proposed mechanism follows the framework of autonomous decentralized control based on local interaction, in which the behavior of the whole system is indirectly controlled by appropriately designing the autonomous actions of the subsystems. As an application example, we demonstrate autonomous decentralized clustering for a two-dimensional lattice network model, and the characteristics and adaptability of the proposed method are shown. In particular, the clusters produced can reflect the environmental situation of each node given by the initial condition.

Speaker change detection involves the identification of the time indices of an audio stream, where the identity of the speaker changes. This paper proposes novel measures for speaker change detection over the centroid model, which divides the feature space into non-overlapping clusters for effective speaker-change comparison. The centroid model is a computationally-efficient variant of the widely-used mixture-distribution based background models for speaker recognition. Experiments on both synthetic and real-world data were performed; the results show that the proposed approach yields promising results compared with the conventional statistical measures.

Non-homogeneous Poisson processes (NHPPs) have gained much popularity in actual software testing phases to estimate the software reliability, the number of remaining faults in software and the software release timing. In this paper, we propose a new modeling approach for the NHPP-based software reliability models (SRMs) to describe the stochastic behavior of software fault-detection processes. The fundamental idea is to apply the equilibrium distribution to the fault-detection time distribution in NHPP-based modeling. We also develop efficient parameter estimation procedures for the proposed NHPP-based SRMs. Through numerical experiments, it can be concluded that the proposed NHPP-based SRMs outperform the existing ones in many data sets from the perspective of goodness-of-fit and prediction performance.

Switch-and-stay combining (SSC) is a simple diversity technique where a single radio frequency (RF) chain is connected to one of several antenna branches and stays there if the channel quality is satisfied or otherwise switches to a new branch. Compared with Selection Combining (SC), SSC requires less overhead in channel estimation and antenna selection feedback. In this paper, we analyze the performance of SSC in a time-correlated flat fading channel and with causal channel state information. We derive the general expressions for the distribution of the output signal-to-noise ratio (SNR), outage rate and average bit error rate (ABER) and then the analytical results are compared with the simulation results under the Jakes Rayleigh fading channel. Our results show that (1) For slowly varying channels, L branch SSC can achieve the full diversity order and the same outage rate as SC; (2) Increasing the number of antenna branches can improve the performance of SSC, however, the gain from adding antennas diminishes quickly as the channel variation speed increases. Moreover, to avoid the complexity in optimizing the fixed threshold, we also propose a simple adaptive SSC scheme which has almost the same ABER as the SSC with optimized fixed threshold.

Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In this paper, we propose a novel, efficient algorithm for multi-valued bounded model checking. A notable feature of our algorithm is that it is not based on reduction of multi-values into two-values; instead, it generates a single formula which represents multi-valuedness by a suitable encoding, and asks a standard SAT solver to check its satisfiability. Our experimental results show a significant improvement in the number of variables and clauses and also in execution time compared with the reduction-based one.

In this paper, a logarithmic adaptive quantization projection (LAQP) algorithm for digital watermarking is proposed. Conventional quantization index modulation uses a fixed quantization step in the watermarking embedding procedure, which leads to poor fidelity. Moreover, the conventional methods are sensitive to value-metric scaling attack. The LAQP method combines the quantization projection scheme with a perceptual model. In comparison to some conventional quantization methods with a perceptual model, the LAQP only needs to calculate the perceptual model in the embedding procedure, avoiding the decoding errors introduced by the difference of the perceptual model used in the embedding and decoding procedure. Experimental results show that the proposed watermarking scheme keeps a better fidelity and is robust against the common signal processing attack. More importantly, the proposed scheme is invariant to value-metric scaling attack.