The present paper describes a method for the construction of a zero-correlation zone sequence set from a perfect sequence. Both the cross-correlation function and the side-lobe of the auto-correlation function of the proposed sequence sets are zero for phase shifts within the zero-correlation zone. These sets can be generated from an arbitrary perfect sequence, the length of which is the product of a pair of odd integers ((2n+1)(2k+1) for k ≥ 1 and n ≥ 0). The proposed sequence construction method can generate an optimal zero-correlation zone sequence set that achieves the theoretical bounds of the sequence member size given the size of the zero-correlation zone and the sequence period. The peak in the out-of-phase correlation function of the constructed sequences is restricted to be lower than the half of the power of the sequence itself. The proposed sequence sets could successfully provide CDMA communication without co-channel interference, or, in an ultrasonic synthetic aperture imaging system, improve the signal-to-noise ratio of the acquired image.

This letter proposes a motion information inferring scheme for multi-view video coding motivated by the idea that the aspect of motion vector between the corresponding positions in the neighboring view pair is quite similar. The proposed method infers the motion information from the corresponding macroblock in the neighboring view after RD optimization with the existing prediction modes. This letter presents evaluation showing that the method significantly enhances the efficiency especially at high bit rates.

This paper proposes the minimum transition random X-filling (MTR-fill) technique, which is a new X-filling method, to reduce the amount of power dissipation during scan-based testing. In order to model the amount of power dissipated during scan load/unload cycles, the total weighted transition metric (TWTM) is introduced, which is calculated by the sum of the weighted transitions in a scan-load of a test pattern and a scan-unload of a test response. The proposed MTR-fill is implemented by simulated annealing method. During the annealing process, the TWTM of a pair of test patterns and test responses are minimized. Simultaneously, the MTR-fill attempts to increase the randomness of test patterns in order to reduce the number of test patterns needed to achieve adequate fault coverage. The effectiveness of the proposed technique is shown through experiments for ISCAS'89 benchmark circuits.

In our previous study, a distortion measure based variable bit rate (DM-VBR) scheme in waveform interpolation (WI) coders was proposed. In this paper, the repetition method is proposed to estimate non-transmitted parameters instead of the extrapolation method. For the further reduction of slowly evolving waveform (SEW) bit rates, the dimensions of the past parameters, which are different from those of the current parameters, are converted to match the dimension of the current ones. Distortions between interpolated sub-frames and original sub-frames are measured for the reduction of the SEW parameters. And the usefulness of several other distortion measures is also investigated instead of the simple log spectral distortion. Experimental results show that the coder adopting the new schemes offers above 41% bit rate reduction with almost unnoticeable output speech degradation.

We have proposed a random curved surface model as a new mathematical concept which enables the expression of spatial correlation. The model gives us an appropriate methodology to deal with the systematic components of device variation in an LSI chip. The key idea of the model is the fitting of a polynomial to an array of Gaussian random numbers. The curved surface is expressed by a new extension from the Legendre polynomials to form two-dimensional formulas. The formulas were proven to be suitable to express the spatial correlation with reasonable computational complexity. In this paper, we show that this approach is useful in analyzing characteristics of device variation of actual chips by using experimental data.

A packet detection method for zero-padded orthogonal frequency division multiplexing (OFDM) transmission is presented. The proposed algorithm effectively conducts packet detection by employing both an M-sample time delayed cross correlation value, and a received signal power calculated by using the received input samples corresponding to the zero padding (ZP) intervals or less.

This paper proposes a method to generate exceptional scenarios from a normal scenario written with a scenario language. This method includes (1) generation of exceptional plans and (2) generation of exceptional scenario by a user's selection of these plans. The proposed method enables users to decrease the omission of the possible exceptional scenarios in the early stages of development. The method will be illustrated with some examples.

Conventional narrowband interference (NBI) rejection algorithms often assumed perfect pseudo-noise (PN) code synchronization. The functions of NBI rejection and code tracking are performed separately and independently by an adaptive filter and a code tracking loop, respectively. This paper presents two new receiver structures for direct sequence spread spectrum (DS/SS) systems, one operates in coherent mode and the other operates in noncoherent mode. Both receivers are designed to suppress NBI and minimize tracking jitter. Numerical results show that the proposed coherent receiver performs as good as the conventional receiver that uses an LMS NBI rejection filter with zero tracking jitter. The noncoherent receiver, when compared with the coherent one, suffers less than 3 dB degradation for bit error probability smaller than 10-3.

Timing closure in LSI design is becoming more and more difficult. But the conventional interconnect RC extraction method has over-margins caused by its corner conditions settings. In this paper, statistical corner conditions using the independence of variations between process parameters and between interconnect layers are proposed, with examinations using the measurement data. As a result of the method, the fast-to-slow guardband decreases by half in average, compared to the conventional method. The proposed method is ready for implementation to LPE tools.

In video compression, the information transmitted from the encoder to the decoder can be classified into two categories: side information, which carries action instructions to be performed, and data such as the residual error of the texture. As video compression technology has matured, better compression has been achieved by increasing the ratio of side information to data, while reducing the overall bit rate. However, there is a limit to this method because the side information becomes a significant fraction of the overall bit rate. In recent video compression technologies, the decoder tends to share the burden of the decision making in order to achieve a higher compression ratio. To further improve the coding efficiency, we tried to provide the decoder with a more active role in reducing the amount of data. According to this approach, by using reconstructed pixels that surround a target block to produce a better sample predictor of the target block, the amount of side information and the residual error of the texture are reduced. Furthermore, multiple candidates of the sample predictor are utilized to create a better sample predictor without increasing the amount of side information. In this paper, we employ a template matching method that makes the decoder more active. The template matching method is applied to the conventional video codec to improve the prediction performance of intra, inter, and bi-directional pictures in video. The results show that improvements in coding efficiency up to 5.8% are achieved.

This paper proposes a likelihood estimation method for reduced-complexity maximum-likelihood (ML) detectors in a multiple-input multiple-output (MIMO) spatial-multiplexing (SM) system. Reduced-complexity ML detectors, e.g., Sphere Decoder (SD) and QR decomposition (QRD)-M algorithm, are very promising as MIMO detectors because they can estimate the ML or a quasi-ML symbol with very low computational complexity. However, they may lose likelihood information about signal vectors having the opposite bit to the hard decision and bit error rate performance of the reduced-complexity ML detectors are inferior to that of the ML detector when soft-decision decoding is employed. This paper proposes a simple estimation method of the lost likelihood information suitable for the reduced-complexity ML detectors. The proposed likelihood estimation method is applicable to any reduced-complexity ML detectors and produces accurate soft-decision bits. Computer simulation confirms that the proposed method provides excellent decoding performance, keeping the advantage of low computational cost of the reduced-complexity ML detectors.

Realistic representations using extremely high quality images are becoming increasingly popular. For example, digital cinemas can now display moving pictures composed of high-resolution digital images. Although these applications focus on increasing the spatial resolution only, higher frame-rates are being considered to achieve more realistic representations. Since increasing the frame-rate increases the total amount of information, efficient coding methods are required. However, its statistical properties are not clarified. This paper establishes for high frame-rate video a mathematical model of the relationship between frame-rate and bit-rate. A coding experiment confirms the validity of the mathematical model.

By utilizing the second and fourth order linear prediction errors, a novel estimator for a single noisy sinusoid is devised. The frequency estimate is obtained from a solving a cubic equation and a simple root selection procedure is provided. Asymptotical variance of the estimated frequency is derived and confirmed by computer simulations. It is demonstrated that the proposed estimator is superior to the reformed Pisarenko harmonic decomposer, which is the improved version of Pisarenko harmonic decomposer.

The letter proposes a novel subsampling-based digital image watermarking scheme resisting the permutation attack. The subsampling-based watermarking schemes have drawn great attention for their convenience and effectiveness in recent years, but the traditional subsampling-based watermarking schemes are very vulnerable to the permutation attack. In this letter, the watermark information is embedded in the average values of the 1-level DWT coefficients to resist the permutation attack. The concrete embedding process is achieved by the quantization-based method. Experimental results show that the proposed scheme can resist not only the permutation attack but also some common image processing attacks.

In this paper, we propose a recursive filtering algorithm to restore monochromatic images which are corrupted by general dependent additive noise. It is assumed that the equation which describes the image field is not available and a filtering algorithm is obtained using the information provided by the covariance functions of the signal, noise that affects the measurement equation, and the fourth-order moments of the signal. The proposed algorithm is obtained by an innovation approach which provides a simple derivation of the least mean-squared error linear estimators. The estimation of the grey level in each spatial coordinate is made taking into account the information provided by the grey levels located on the row of the pixel to be estimated. The proposed filtering algorithm is applied to restore images which are affected by general signal-dependent additive noise.

This paper studies a spiking neuron circuit with triangular base signal. The circuit can output rich spike-trains and the dynamics can be analyzed using a one-dimensional piecewise linear map. This system exhibits period doubling bifurcation, tangent bifurcation, super-stable periodic orbit bifurcation and so on. These phenomena can be characterized based on the inter-spike intervals. Using the maps, we can analyze the phenomena precisely. By presenting a simple test circuit, typical phenomena are confirmed experimentally.

This study proposes a method to decompose a signal into a set of periodic signals. The proposed decomposition method imposes a penalty on the resultant periodic subsignals in order to improve the sparsity of decomposition and avoid the overestimation of periods. This penalty is defined as the weighted sum of the l2 norms of the resultant periodic subsignals. This decomposition is approximated by an unconstrained minimization problem. In order to solve this problem, a relaxation algorithm is applied. In the experiments, decomposition results are presented to demonstrate the simultaneous detection of periods and waveforms hidden in signal mixtures.

A sound localization method in the proximal region is proposed, which is based on a low-cost 3D sound localization algorithm with the use of head-related transfer functions (HRTFs). The auditory parallax model is applied to the current algorithm so that more accurate HRTFs can be used for sound localization in the proximal region. In addition, head-shadowing effects based on rigid-sphere model are reproduced in the proximal region by means of a second-order IIR filter. A subjective listening test demonstrates the effectiveness of the proposed method. Embedded system implementation of the proposed method is also described claiming that the proposed method improves sound effects in the proximal region only with 5.1% increase of memory capacity and 8.3% of computational costs.

Error concealment at a decoder is an efficient method to reduce the degradation of visual quality caused by channel errors. In this paper, we propose a novel spatio-temporal error concealment algorithm based on the spatial-temporal fading (STF) scheme which has been recently introduced. Although STF achieves good performance for the error concealment, several drawbacks including blurring still remain in the concealed blocks. To alleviate these drawbacks, in the proposed method, hybrid approaches with adaptive weights are proposed. First, the boundary matching algorithm and the decoder motion vector estimation which are well-known temporal error concealment methods are adaptively combined to compensate for the defect of each other. Then, an edge preserved method is utilized to reduce the blurring effects caused by the bilinear interpolation for spatial error concealment. Finally, two concealed results obtained by the hybrid spatial and temporal error concealment are pixel-wisely blended with adaptive weights. Experimental results exhibit that the proposed method outperforms conventional methods including STF in terms of the PSNR performance as well as subjective visual quality, and the computational complexity of the proposed method is similar to that of STF.

This paper proposes a self-test method of coarse grain dynamically reconfigurable processors (DRPs) without hardware overhead. In the method, processor elements (PEs) compose a test frame, which consists of test pattern generators (TPGs), processor elements under test (PEUTs) and response analyzers (RAs), while testing themselves one another by changing test frames appropriately. We design several test frames with different structures, and discuss the relationship of the structures to the numbers of contexts and test frames for testing all the functions of PEs. A case study shows that there exists an optimal test frame which minimizes the test application time under a constraint.