To provide very high quality and/or high resolution video content under limited bandwidth conditions for transmission or storage, the high efficiency video coding (HEVC) has been recently finalised by the joint collab...
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To provide very high quality and/or high resolution video content under limited bandwidth conditions for transmission or storage, the high efficiency video coding (HEVC) has been recently finalised by the joint collaborative team on video coding. In this study, the authors propose a fast prediction unit (PU) decision method to reduce the computational complexity of HEVC encoder. They use an early PU decision in each coding unit-level based on spatio-temporal analyses and depth correlations. They also consider a classification of motion activity. Experimental results show that the encoding complexity can be reduced by up to 38% on average in the random access main profile configuration with only a small bit-rate increment and a peak signal to noise ratio (PSNR) decrement, compared to high efficiency video coding test model (HM) 7.0 reference software.
In this paper, we show how to compute in O(n(2))steps the Fourier coefficients associated with the Gelfand-Levitan approach for discrete Sobolev orthogonal polynomials on the unit circle when the support of the discre...
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In this paper, we show how to compute in O(n(2))steps the Fourier coefficients associated with the Gelfand-Levitan approach for discrete Sobolev orthogonal polynomials on the unit circle when the support of the discrete component involving derivatives is located outside the closed unit disk. As a consequence, we deduce the outer relative asymptotics of these polynomials in terms of those associated with the original orthogonality measure. Moreover, we show how to recover the discrete part of our Sobolev inner product. (C) 2013 Elsevier Inc. All rights reserved.
This paper concerns the hardness of approximating the closest vector in a lattice with preprocessing in l1norm,and gives a polynomial time algorithm for GapCVPPγin l1norm with gapγ=O(n/log n).The gap is smaller than...
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This paper concerns the hardness of approximating the closest vector in a lattice with preprocessing in l1norm,and gives a polynomial time algorithm for GapCVPPγin l1norm with gapγ=O(n/log n).The gap is smaller than that obtained by simply generalizing the approach given by Aharonov and *** main technical ingredient used in this paper is the discrete Laplace distribution on lattices which may be of independent interest.
Traditional results in subrecursion theory are integrated with the recent work in "predicative recursion" by defining a simple ranking rho of all primitive recursive functions. The hierarchy defined by this ...
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Traditional results in subrecursion theory are integrated with the recent work in "predicative recursion" by defining a simple ranking rho of all primitive recursive functions. The hierarchy defined by this ranking coincides with the Grzegorczyk hierarchy at and above the linear-space level. Thus, the result is like an extension of the Schwichtenberg-Muller theorems. When primitive recursion is replaced by recursion on notation, the same series of classes is obtained except with the polynomial time computable functions at the first level.
Recently, the improved simple set-membership affine projection (IS-SM-AP) algorithm has been proposed in order to exploit sparsity in system models. Although its update equation resembles that of the set-membership af...
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Recently, the improved simple set-membership affine projection (IS-SM-AP) algorithm has been proposed in order to exploit sparsity in system models. Although its update equation resembles that of the set-membership affine projection (SM-AP) algorithm, the IS-SM-AP algorithm has two fundamental advantages over the SM-AP algorithm: (i) it can exploit sparsity in system models and (ii) its computational complexity is lower. Up to now, the properties of this algorithm have been addressed only through numerical simulations, and no analytical study has been presented. To fill this gap, in this study, the authors analyse the steady-state mean squared error of the IS-SM-AP algorithm using the energy conservation method. Furthermore, some important implementation issues are addressed, and a time-varying parameter for the discard function is proposed. Finally, the authors present numerical results corroborating the theoretical analysis and the effectiveness of the proposed time-varying parameter.
This paper presents an efficient approach to statistical leakage analysis (SLA) that can estimate the arbitrary n-sigma leakage currents of the VLSI system for the probability density function (PDF) of a lognormal dis...
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This paper presents an efficient approach to statistical leakage analysis (SLA) that can estimate the arbitrary n-sigma leakage currents of the VLSI system for the probability density function (PDF) of a lognormal distribution. Unlike existing SLA approaches, the proposed method uses deterministic cell leakage models and gate-level deterministic leakage analysis, and thus, provides significantly reduced analysis complexity. Providing the n-sigma chip leakage current for the PDF of WM-based SLA with a computational complexity of O(N), where N is the number of cells in a chip, the proposed approach is a promising candidate for the analysis of recent technology (comprising billions of logic cells in a chip) to address the high-complexity of conventional approaches to SLA. Compared to conventional WM-based SLA, when the value of n was 5.1803, 3.6022, and 2.8191, the average absolute errors of n-sigma chip leakage current exhibited by the proposed approach were 5.08%, 4.73%, and 4.45%, respectively. (C) 2013 Elsevier Ltd. All rights reserved.
Detection of weak manoeuvring targets has always been an important yet challenging task for radar signal processing. One primary reason is that target variable motions within a coherent processing interval generate en...
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Detection of weak manoeuvring targets has always been an important yet challenging task for radar signal processing. One primary reason is that target variable motions within a coherent processing interval generate energy migrations across multiple resolution bins, which severely deteriorate the parameter estimation performance. The problem is compounded by an increasingly complex surveillance environment, as well as more affordable and pervasive than ever small targets such as drones. In this work, a coarse-to-fine strategy for the detection of weak manoeuvring targets is designed. First, a coarse estimation of the chirp parameter in an extended unambiguous range using a novel coprime segmented discrete polynomial-phase transform is coherently integrated and derived. Sparse fractional Fourier transform is then employed to refine the coarse estimation at a significantly reduced computational complexity. The proposed scheme achieves an efficient and reliable weak target detection, while requires no a priori knowledge on the motion parameters, which is verified by the simulation results.
Aiming at minimizing the transmit power of orthogonal frequency-division multiplexing (OFDM) systems subject to the target data rate, the target bit error rate (BER), the maximum allowable power per subcarrier, and th...
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Aiming at minimizing the transmit power of orthogonal frequency-division multiplexing (OFDM) systems subject to the target data rate, the target bit error rate (BER), the maximum allowable power per subcarrier, and the-maximum allowable size of constellations, we present a couple of new discrete bitloading algorithms, named efficient bit filling (EBF) and efficient bit removal (EBR), which are based on our new idea of group-by-group bit filling. Both EBF and EBR perform bit loading in two stages and are able to converge to the optimal bit-allocation profile. In the first stage, an intermediate bit-allocation profile, which is tightly close to the final bit-allocation profile, is obtained by using our proposed group-by-group bit filling (for EBF) or group-by-group bit removal (for EBR). In the second stage, the well-known greedy bit filling (for EBF) or greedy bit removal (for EBR) is performed for the remaining bits (usually of a small size). Analytical and numerical results reveal that the proposed algorithms converge to the optimal bit allocation with much lower computational complexities than existing optimal algorithms. It is also shown that the proposed algorithms outperform typical suboptimal algorithms in power efficiency with relatively higher computational complexities.
Analysis/synthesis systems designed for low bit rate image coding, their impact on overall system quality, and their computational complexity are discussed. The investigation focuses on the design of analysis/synthesi...
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Analysis/synthesis systems designed for low bit rate image coding, their impact on overall system quality, and their computational complexity are discussed. The investigation focuses on the design of analysis/synthesis systems for image coding and the perceptual impact of these systems at low bit rates. Two objectives are emphasized in developing these systems: confining the total size of the subband images to be equal to the original image size, and designing the filters so that perceptual distortion is not introduced by the analysis/synthesis system. Methods based on circular convolution and symmetric extensions are developed and discussed in detail. The theory, design, and implementation of both recursive and nonrecursive filtering systems are discussed. Methods are introduced which display advantages over conventional quadrature mirror filter based approaches.< >
High computational complexity and inadequate parallelism have deterred the use of subspace-based algorithms in real-time systems, Recently, we proposed a new class of fast subspace tracking (FST) algorithms that overc...
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High computational complexity and inadequate parallelism have deterred the use of subspace-based algorithms in real-time systems, Recently, we proposed a new class of fast subspace tracking (FST) algorithms that overcome these problems by exploiting the matrix structure inherent in multisensor processing, These algorithms simultaneously track an orthonormal basis for the signal subspace and preserve signal eigenstructure information while requiring only O(Nr) operations per update (where N is the number of channels, and r is the effective rank), Because of their low computational complexity, these algorithms have applications in both recursive and block data processing, Because they preserve the signal eigenstructure as well as compute an orthonormal basis for the signal subspace, these algorithms may be used in a wide range of sensor array applications including bearing estimation, beamforming, and recursive least squares, In this paper, we will present a detailed description of the FST algorithm and its rank adaptive variation (RA-FST) as well as recent enhancements, We also demonstrate FST's rapid convergence properties in a number of application scenarios.
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