In this work, a high efficiency coding unit (CU) size decision algorithm is proposed for high efficiency video coding (HEVC) inter coding. The CU splitting or non-splitting is modeled as a binary classification problem based on probability graphical model (PGM). This method incorporates two sub-methods: CU size termination decision and CU size skip decision. This method focuses on the trade-off between encoding efficiency and encoding complexity, and it has a good performance. Particularly in the high resolution application, simulation results demonstrate that the proposed algorithm can reduce encoding time by 53.62%-57.54%, while the increased BD-rate are only 1.27%-1.65%, compared to the HEVC software model.

We propose subquadratic space complexity multipliers for any finite field $mathbb{F}_{q^n}$ over the base field $mathbb{F}_q$ using the Dickson basis, where q is a prime power. It is shown that a field multiplication in $mathbb{F}_{q^n}$ based on the Dickson basis results in computations of Toeplitz matrix vector products (TMVPs). Therefore, an efficient computation of a TMVP yields an efficient multiplier. In order to derive efficient $mathbb{F}_{q^n}$ multipliers, we develop computational schemes for a TMVP over $mathbb{F}_{q}$. As a result, the $mathbb{F}_{2^n}$ multipliers, as special cases of the proposed $mathbb{F}_{q^n}$ multipliers, have lower time complexities as well as space complexities compared with existing results. For example, in the case that n is a power of 3, the proposed $mathbb{F}_{2^n}$ multiplier for an irreducible Dickson trinomial has about 14% reduced space complexity and lower time complexity compared with the best known results.

In this letter, we investigate the problem of feedforward timing estimation for burst-mode satellite communications. By analyzing the correlation property of frame header (FH) acquisition in the presence of sampling offset, a novel data-aided feedforward timing estimator that utilizes the correlation peaks for interpolating the fractional timing offset is proposed. Numerical results show that even under low signal-to-noise ratio (SNR) and small rolloff factor conditions, the proposed estimator can approach the modified Cramer-Rao bound (MCRB) closely. Furthermore, this estimator only requires two samples per symbol and can be implemented with low complexity with respect to conventional data-aided estimators.

This paper presents a wideband digital predistortion (DPD) architecture suitable for wideband wireless systems, such as IEEE 802.11ad/WiGig, where low oversampling ratio of the digital-to-analog converter (DAC) is a bottleneck for available linearization bandwidth. In order to overcome the bandwidth limitation in the conventional DPD, the proposed DPD introduces a complex coefficient filter in the DPD signal processing, which enables it to achieve asymmetric linearization. This approach effectively suppresses one side of adjacent channel leakages with twice the bandwidth as compared to the conventional DPD. The concept is verified through system simulation and measurements. Using a scaled model of a 2 GHz RF carrier frequency, the measurement shows a 4.2 dB advantage over the conventional DPD in terms of adjacent channel leakage.

The scan segmentation method is an efficient solution to deal with the test power problem; However, the use of multiple capture cycles may cause capture violations, thereby leading to fault coverage loss. This issue is much more severe in at-speed testing. In this paper, two scan partition schemes based on complex networks clustering ara proposed to minimize the capture violations without increasing test-data volume and extra area overhead. In the partition process, we use a more accurate notion, spoiled nodes, instead of violation edges to analyse the dependency of flip-flops (ffs), and we use the shortest-path betweenness (SPB) method and the Laplacian-based graph partition method to find the best combination of these flip-flops. Beyond that, the proposed methods can use any given power-unaware set of patterns to test circuits, reducing both shift and capture power in at-speed testing. Extensive experiments have been performed on reference circuit ISCAS89 and IWLS2005 to verify the effectiveness of the proposed methods.

Based on the generalized cyclotomy of order two with respect to n=p1e1+1p2e2+1…ptet+1, where p1, p2, …,pt are pairwise distinct odd primes and e1, e2,…, et are non-negative integers satisfying gcd (piei (pi-1), pjej (pj-1)) = 2 for all i ≠ j, this paper constructs a new family of generalized cyclotomic sequences of order two with length n and investigates their linear complexity. In the view of cascade theory, this paper obtains the linear complexity of a representative sequence.

Some diffusive and recurrence properties of Lorentz Lattice Gas Cellular Automata (LLGCA) have been expensively studied in terms of the densities of some of the left/right static/flipping mirrors/rotators. In this paper, for any combination S of these well known scatters, we study the computational complexity of the following problem which we call PERIODICITY on the S-model: given a finite configuration that distributes only those scatters in S, whether a particle visits the starting position periodically or not. Previously, the flipping mirror model and the occupied flipping rotator model have been shown unbounded, i.e. the process is always diffusive [17]. On the other hand, PERIODICITY is shown PSPACE-complete in the unoccupied flipping rotator model [21]. In this paper, we show that PERIODICITY is PSPACE-compete in any S-model that is neither occupied, unbounded, nor static. Particularly, we prove that PERIODICITY in any unoccupied and bounded model containing flipping mirror is PSPACE-complete.

The information maximization (Infomax) based on information entropy theory is a class of methods that can be used to blindly separate the sources. Torkkola applied the Infomax criterion to blindly separate the mixtures where the sources have been delayed with respect to each other. Compared to the frequency domain methods, this time domain method has simple adaptation rules and can be easily implemented. However, Torkkola's method works only in the real valued field. In this letter, the Infomax for blind separation of the delayed sources is extended to the complex case for processing of complex valued signals. Firstly, based on the gradient ascent the adaptation rules for the parameters of the unmixing network are derived and the steps of algorithm are given. Then, a measurement matrix is constructed to evaluate the separation performance. The results of computer experiment support the extended algorithm.

This paper proposes a fast mode decision technique for intra prediction of High Efficiency Video Coding (HEVC) based on a reliability metric for motion vectors (RMMV). Since such a decision problem can be regarded as a kind of pattern classification, an efficient classifier is required for the reduction of computation complexity. This paper employs the RMMV as a classifier because the RMMV can efficiently categorize image blocks into flat(uniform), active, and edge blocks, and can estimate the direction of an edge block as well. A local search for angular modes is introduced to further speed up the decision process. An experiment shows the advantage of our technique over other techniques.

The power grid defines one of the most important technological networks of our times and has been widely studied as a kind of complex network. It has been developed for more than one century and becomes an extremely huge and seemingly robust system. But it becomes extremely fragile as well because some unexpected minimal failures may lead to sudden and massive blackouts. Many works have been carried out to investigate the structural vulnerability of power grids from the topological point of view based on the complex network theory. This Letter focuses on the structural vulnerability of the power grid under the effect of selective node removal. We propose a new kind of node centrality called overall information centrality (OIC) to guide the node removal attack. We test the effectiveness of our centrality in guiding the node removal based on several IEEE power grids. Simulation results show that, compared with other node centralities such as degree centrality (DC), betweenness centrality (BC) and closeness centrality (CC), our OIC is more effective to guide the node removal and can destroy the power grid in less steps.

Many selected mapping (SLM) schemes have been proposed to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signal sequences. In this paper, an efficient selection (ES) method of the OFDM signal sequence with minimum PAPR among many alternative OFDM signal sequences is proposed; it supports various SLM schemes. Utilizing the fact that OFDM signal components can be sequentially generated in many SLM schemes, the generation and PAPR observation of the OFDM signal sequence are processed concurrently. While the u-th alternative OFDM signal components are being generated, by applying the proposed ES method, the generation of that alternative OFDM signal components can be interrupted (or stopped) according to the selection criteria of the best OFDM signal sequence in the considered SLM scheme. Such interruption substantially reduces the average computational complexity of SLM schemes without degradation of PAPR reduction performance, which is confirmed by analytical and numerical results. Note that the proposed method is not an isolated SLM scheme but a subsidiary method which can be easily adopted in many SLM schemes in order to further reduce the computational complexity of considered SLM schemes.

In this paper, we propose an efficient regularized zero-forcing (RZF) precoding method that has lower hardware resource requirements and produces a shorter delay to the first transmitted symbol compared with truncated polynomial expansion (TPE) that is based on Neumann series in massive multiple-input multiple-output (MIMO) systems. The proposed precoding scheme, named matrix decomposition-polynomial expansion (MDPE), essentially applies a matrix decomposition algorithm based on polynomial expansion to significantly reduce full matrix multiplication computational complexity. Accordingly, it is suitable for real-time hardware implementations and high-mobility scenarios. Furthermore, the proposed method provides a simple expression that links the optimization coefficients to the ratio of BS/UTs antennas (β). This approach can speed-up the convergence to the matrix inverse by a matrix polynomial with small terms and further reduce computation costs. Simulation results show that the MDPE scheme can rapidly approximate the performance of the full precision RZF and optimal TPE algorithm, while adaptively selecting matrix polynomial terms in accordance with the different β and SNR situations. It thereby obtains a high average achievable rate of the UTs under power allocation.

In this paper, an iterative optimal method is proposed to design the prototype filters for a fast filter bank (FFB) with low complexity, aiming to control the optimum ripple magnitude tolerance of each filter according to the overall specifications. This problem is formulated as an optimization problem for which the total number of multiplications is to be minimized subject to the constrained ripple in the passband and stopband. In the following, an iterative solution is proposed to solve this optimization problem for the purpose of obtaining the impulse response coefficients with low complexity at each stage. Simulations are conducted to verify the performance of the proposed scheme and show that compared with the original method, the proposed scheme can reduce about 24.24% of multiplications. In addition, the proposed scheme and the original method provide similar mean square error (MSE) and the mean absolute error (MAE) of the frequency response.

The controllability of complex networks has attracted increasing attention within various scientific fields. Many power grids are complex networks with some common topological characteristics such as small-world and scale-free features. This Letter investigate the controllability of some real power grids in comparison with classical complex network models with the same number of nodes. Several conclusions are drawn after detailed analyses using several real power grids together with Erdös-Rényi (ER) random networks, Wattz-Strogatz (WS) small-world networks, Barabási-Albert (BA) scale-free networks and configuration model (CM) networks. The main conclusion is that most driver nodes of power grids are hub-free nodes with low nodal degree values of 1 or 2. The controllability of power grids is determined by degree distribution and heterogeneity, and power grids are harder to control than WS networks and CM networks while easier than BA networks. Some power grids are relatively difficult to control because they require a far higher ratio of driver nodes than ER networks, while other power grids are easier to control for they require a driver node ratio less than or equal to ER random networks.

The ordered successive interference cancellation (OSIC) detector based on the minimum mean square error (MMSE) criterion has been proved to be a low-complexity detector with efficient bit error rate (BER) performance. As the well-known MMSE-Based OSIC detector, the MMSE-Based vertical Bell Laboratories Layered Space-Time (VBLAST) detector, whose computational complexity is cubic, can not attain the minimum BER performance. Some approaches to reducing the BER of the MMSE-Based VBLAST detector have been contributed, however these improvements have large computational complexity. In this paper, a low complexity MMSE-Based OSIC detector called MMSE-OBEP (ordering based on error probability) is proposed to improve the BER performance of the previous MMSE-Based OSIC detectors, and it has cubic complexity. The proposed detector derives the near-exact error probability of the symbols in the MMSE-Based OSIC detector, thus giving priority to detect the symbol with the smallest error probability can minimize the error propagation in the MMSE-Based OSIC detector and enhance the BER performance. We show that, although the computational complexity of the proposed detector is cubic, it can provide better BER performance than the previous MMSE-Based OSIC detector.

Amplify-and-forward (AF) relay multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems can achieve high data rate and high quality communications. On the other hand, it has to estimate all channels between the source-relay and relay-destination nodes in the destination node. In MIMO/OFDM systems, high time resolution carrier interferometry (HTRCI) has been proposed to achieve an accurate channel estimation (CE) with a small number of pilot signals. However, since it has many interferences, an accurate CE is not obtained and the system performance is degraded in AF relay MIMO/OFDM systems. Therefore, in this paper, we propose the complex HTRCI (C-HTRCI) pilot signal and the enhanced minimum mean square error (E-MMSE) equalization to achieve an accurate CE and to improve the system performance for AF relay MIMO/OFDM systems.

A field multiplication in the extended binary field is often expressed using Toeplitz matrix-vector products (TMVPs), whose matrices have special properties such as symmetric or triangular. We show that such TMVPs can be efficiently implemented by taking advantage of some properties of matrices. This yields an efficient multiplier when a field multiplication involves such TMVPs. For example, we propose an efficient multiplier based on the Dickson basis which requires the reduced number of XOR gates by an average of 34% compared with previously known results.

The advanced front-end (AFE) for automatic speech recognition (ASR) was standardized by the European Telecommunications Standards Institute (ETSI). The AFE provides speech enhancement realized by an iterative Wiener filter (IWF) in which a smoothed FFT spectrum over adjacent frames is used to design the filter. We have previously proposed robust time-varying complex Auto-Regressive (TV-CAR) speech analysis for an analytic signal and evaluated the performance of speech processing such as F0 estimation and speech enhancement. TV-CAR analysis can estimate more accurate spectrum than FFT, especially in low frequencies because of the nature of the analytic signal. In addition, TV-CAR can estimate more accurate speech spectrum against additive noise. In this paper, a time-invariant version of wide-band TV-CAR analysis is introduced to the IWF in the AFE and is evaluated using the CENSREC-2 database and its baseline script.

The next generation high efficiency video coding (HEVC) standard achieves high performance by extending the encoding block to 64×64. There are some parallel tools to improve the efficiency for encoder and decoder. However, owing to the dependence of the current prediction block and surrounding block, parallel processing at CU level and Sub-CU level are hard to achieve. In this paper, focusing on the spatial motion vector prediction (SMVP) and temporal motion vector prediction (TMVP), parallel improvement for spatio-temporal prediction algorithms are presented, which can remove the dependency between prediction coding units and neighboring coding units. Using this proposal, it is convenient to process motion estimation in parallel, which is suitable for different parallel platforms such as multi-core platform, compute unified device architecture (CUDA) and so on. The simulation experiment results demonstrate that based on HM12.0 test model for different test sequences, the proposed algorithm can improve the advanced motion vector prediction with only 0.01% BD-rate increase that result is better than previous work, and the BDPSNR is almost the same as the HEVC reference software.

Orthogonal frequency division multiplexing (OFDM) channel estimation is the key technique used in broadband wireless networks. The Doppler frequency caused by fast mobility environments will cause inter-carrier interference (ICI) and degrade the performance of OFDM systems. Due to the severe ICI, channel estimation becomes a difficult task in higher mobility scenarios. Our aim is to propose a pilot-aided channel estimation method that is robust to high Doppler frequency with low computational complexity and pilot overheads. In this paper, the time duration of each estimate covers multiple consecutive OFDM symbols, named a “window”. A close-form of polynomial channel modeling is derived. The proposed method is initialized to the least squares (LS) estimates of the channels corresponding to the time interval of the pilot symbols within the window. Then, the channel interpolation is performed in the entire window. The results of computer simulations and computation complexity evaluations show that the proposed technique is robust to high Doppler frequency with low computation complexity and low pilot overheads. Compared with the state-of-the-art method and some conventional methods, the new technique proposed here has much lower computational complexity while offering comparable performance.