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23rd International Conference on MultiMedia Modeling (MMM)

作者： Chen, Keji Sun, Jun Guo, Zongming Zhao, Dachuan Peking Univ Inst Comp Sci & Technol Beijing Peoples R China Cooperat Medianet Innovat Ctr Shanghai Peoples R China Adv Micro Devices Co Ltd Beijing Peoples R China

ISBN: (纸本)9783319518145;9783319518138

Integer-pixel Motion Estimation (IME) is one of the fundamental and time-consuming modules in encoding. In this paper, a novel two-step IME algorithm is proposed for High Efficiency Video Coding (HEVC) on a Graphic Processing Unit (GPU). First, the whole search region is roughly investigated with a predefined search pattern, which is analyzed in detail to effectively reduce the complexity. Then, the search result is further refined in the zones only around the best candidates of the first step. By dividing IME into two steps, the proposed algorithm combines the advantage of one-step algorithms in synchronization and the advantage of multiple-step algorithms in complexity. According to the experimental results, the proposed algorithm achieves up to 3.64 times speedup compared with previous representative algorithms, and the search accuracy is maintained at the same time. Since IME algorithm is independent from other modules, it is a good choice for different GPU-based encoding applications.

关键词： High Efficiency VideoCoding (HEVC) Graphics Processing Unit(GPU) Integer-pixelMotionEstimation (IME) two-step algorithm

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Reconstructing Genetic Regulatory Networks Using two-step algorithms with the Differential Equation Models of Neural Networks

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INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES 2018年第4期10卷 823-835页

作者： Chen, Chi-Kan Natl Chung Hsing Univ Dept Appl Math Taichung 402 Taiwan

BackgroundThe identification of genetic regulatory networks (GRNs) provides insights into complex cellular processes. A class of recurrent neural networks (RNNs) captures the dynamics of GRN. algorithms combining the RNN and machine learning schemes were proposed to reconstruct small-scale GRNs using gene expression time *** present new GRN reconstruction methods with neural networks. The RNN is extended to a class of recurrent multilayer perceptrons (RMLPs) with latent nodes. Our methods contain two steps: the edge rank assignment step and the network construction step. The former assigns ranks to all possible edges by a recursive procedure based on the estimated weights of wires of RNN/RMLP (RERNN/RERMLP), and the latter constructs a network consisting of top-ranked edges under which the optimized RNN simulates the gene expression time series. The particle swarm optimization (PSO) is applied to optimize the parameters of RNNs and RMLPs in a two-step algorithm. The proposed RERNN-RNN and RERMLP-RNN algorithms are tested on synthetic and experimental gene expression time series of small GRNs of about 10 genes. The experimental time series are from the studies of yeast cell cycle regulated genes and E. coli DNA repair *** unstable estimation of RNN using experimental time series having limited data points can lead to fairly arbitrary predicted GRNs. Our methods incorporate RNN and RMLP into a two-step structure learning procedure. Results show that the RERMLP using the RMLP with a suitable number of latent nodes to reduce the parameter dimension often result in more accurate edge ranks than the RERNN using the regularized RNN on short simulated time series. Combining by a weighted majority voting rule the networks derived by the RERMLP-RNN using different numbers of latent nodes in step one to infer the GRN, the method performs consistently and outperforms published algorithms for GRN reconstruction on most benchmark time series. The fram

关键词： GRN Reconstruction Gene expression time series RNN RMLP two-step algorithm

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A two-step stabilized finite element algorithm for the Smagorinsky model

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APPLIED MATHEMATICS AND COMPUTATION 2022年 422卷 126971-126971页

作者： Zheng, Bo Shang, Yueqiang Southwest Univ Sch Math & Stat Chongqing 400715 Peoples R China

This study considers an efficient two-step stabilized finite element algorithm for the simulation of Smagorinsky model, which involves solving a stabilized nonlinear Smagorinsky problem by the lowest equal-order P 1 - P 1 finite elements and solving a stabilized linear Smagorinsky problem by the quadratic equal-order P 2 - P 2 finite elements. We theoretically and numerically show that the present two-step algorithm can provide an approximate solution with basically the same accuracy as that of solving the stabilized P 2 - P 2 finite element method, and represent a reduction in CPU time.(c) 2022 Elsevier Inc. All rights reserved.

关键词： Smagorinsky model Stabilized method two-step algorithm Equal-order finite element

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On the Minimax Misclassification Ratio of Hypergraph Community Detection

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IEEE TRANSACTIONS ON INFORMATION THEORY 2019年第12期65卷 8095-8118页

作者： Chien, I. (Eli) Lin, Chung-Yi Wang, I-Hsiang Natl Taiwan Univ Dept Elect Engn Taipei 10617 Taiwan Univ Illinois Dept Elect & Comp Engn Champaign IL 61820 USA Natl Taiwan Univ Grad Inst Commun Engn Taipei 10617 Taiwan CALTECH Dept Elect Engn Pasadena CA 91125 USA

Community detection in hypergraphs is explored. Under a generative hypergraph model called "d-wise hypergraph stochastic block model" (d-hSBM), which naturally extends the stochastic block model (SBM) from graphs to d-uniform hypergraphs, the fundamental limit of the misclassification ratio (the loss function in the community detection problem) is studied. For the converse part, a lower bound of the minimax risk, that is, the minimax expected misclassification ratio, is derived. Asymptotically, it decays exponentially fast to zero as the number of nodes tends to infinity, and the rate function is a weighted combination of several divergence terms, each of which is the Renyi divergence of order 1/2 between two Bernoulli distributions. The Bernoulli distributions involved in the characterization of the rate function are those governing the random instantiation of hyperedges in d-hSBM. For the achievability part, we propose a two-step polynomial-time algorithm which, with high probability, has a misclassification ratio with a decaying exponent that is asymptotically greater than or equal to that of our proposed lower bound. The first step of the algorithm is a hypergraph spectral clustering method, which achieves partial recovery to a certain precision level. The second step is a local refinement method, which leverages the underlying probabilistic model along with parameter estimation from the outcome of the first step. To characterize the asymptotic performance of the proposed algorithm, we first derive a sufficient condition for attaining weak consistency in the hypergraph spectral clustering step. Then, under the guarantee of weak consistency in the first step, we upper bound the loss (with high probability) attained in the local refinement step by an exponentially decaying function of the size of the hypergraph and characterize the decaying rate. Compared to existing works in SBM, the main technical challenge lies in the complex structure of error events since com

关键词： Community detection stochastic block model (SBM) hypergraph clustering asymptotic theory hypergraph Laplacian two-step algorithm

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Calibration of three-axis fluxgate magnetometers with nonlinear least square method

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MEASUREMENT 2013年第4期46卷 1600-1606页

作者： Pang, Hongfeng Li, Ji Chen, Dixiang Pan, Mengchun Luo, Shitu Zhang, Qi Luo, Feilu Natl Univ Def Technol Coll Mechatron Engn & Automat Changsha 410073 Hunan Peoples R China

The accuracy of three-axis magnetometers is limited by different scales, bias of each axis and nonorthogonality between axes, which is usually lower than that of scalar magnetometers. In this paper, the nonlinear least square method is proposed to calibrate three-axis magnetometers. The validity of this method was proved by simulation, in which the estimated parameters of the error model are close to prearranged parameters. In experiment, a three-axis fluxgate magnetometer (DM-050), a two dimensional nonmagnetic rotation equipment and a proton magnetometer (GSM-19T) were used. The scalar value of magnetic field was obtained by proton magnetometer and considered to be the true value. The calibration performance of unscented Kalman filter (UKF), two-step algorithm and nonlinear least square were compared. Experimental results show that the error average and standard deviation of nonlinear least square are the least among the three methods. After calibration, the average of scalar error is reduced from -76.2 nT to -0.00093 nT and the standard deviation is reduced from 10.832 nT to 4.298 nT. The results suggest an effective way for the calibration of three-axis fluxgate magnetometers. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Three-axis magnetometers Nonlinear least square Unscented Kalman filter two-step algorithm Nonmagnetic rotation equipment

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Dynamic Unsourced Random Access With Massive MIMO

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2024年第8期23卷 9460-9473页

作者： Jiang, Jia-Cheng Wang, Hui-Ming Xi An Jiao Tong Univ Sch Informat & Commun Engn Xian 710049 Shaanxi Peoples R China Minist Educ Key Lab Intelligent Networks & Network Secur Xian 710049 Shaanxi Peoples R China

In this paper, we propose a novel dynamic unsourced random access (URA) framework for massive multiple-input multiple-output (MIMO) uplink access. Unlike the existing studies, where the quasi-static channel models and the unchanged user states (active or idle) are assumed, we take the dynamics in both the channels and the states of user devices into consideration. Such a framework supports the high mobility of user devices, and facilitates their abrupt terminates and accesses during the whole transmission process. To model the dynamics, we adopt steady-state Gaussian Markov processes for all the channel coefficients of user devices, and introduce a series of latent variables to indicate the user states. We design a two-step algorithm, including the approximate message passing (AMP)-based inner decoding algorithm and the variational message passing (VMP)-based outer decoding algorithm, to decode the information sequences for all the user devices that have accessed the network. Simulation results show that our proposed method outperforms all the baselines when there are dynamics in the channels of user devices, and our proposed method has robustness to deal with the abrupt changes of user states by equipping the large number of antennas at the base station.

关键词： Dynamic massive unsourced access Massive multiple-input multiple-output (MIMO) variational message passing (VMP) approximate message passing (AMP) two-step algorithm Dynamic massive unsourced access Massive multiple-input multiple-output (MIMO) variational message passing (VMP) approximate message passing (AMP) two-step algorithm

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Practical linear precoder design for finite alphabet multiple-input multiple-output orthogonal frequency division multiplexing with experiment validation

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IET COMMUNICATIONS 2013年第9期7卷 836-847页

作者： Zheng, Yahong Rosa Wang, Mingxi Zeng, Weiliang Xiao, Chengshan Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65409 USA

A low complexity precoding method is proposed for practical multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. Based on the two-step optimal precoder design algorithm that maximises the lower bound of the mutual information with finite-alphabet inputs, the proposed method simplifies the precoder design by fixing the right singular vectors of the precoder matrix, eliminating the iterative optimisation between the two steps, and discretising the search space of the power allocation vector. For a 4 x 4 channel, the computational complexity of the proposed precoder design is reduced to 3 and 6% of that required by the original two-step algorithm with quadrature phase shift keying (QPSK) and 8 phase-shift keying (8PSK), respectively. The proposed method achieves nearly the same mutual information as the two-step iterative algorithm for a large range of signal-to-noise ratio (SNR) region, especially for large MIMO size and/or high constellation systems. The proposed precoding design method is applied to a 2 x 2 MIMO-OFDM system with 2048 subcarriers by designing 1024 precoders for extended channel matrices of size 4 x 4. A transceiver test bed implements these precoding matrices in comparison with other existing precoding schemes. Indoor experiments are conducted for fixed-platform non-line-of-sight channels, and the data processing results show that the proposed precoding method achieves the lowest bit error rate compared with maximum diversity, classic water-filling and channel diagonalisation methods.

关键词： channel coding codecs computational complexity indoor radio iterative methods linear codes MIMO communication multiplexing OFDM modulation optimisation phase shift keying precoding radio transceivers transceivers channel diagonalisation methods water-filling methods maximum diversity bit error rate precoding method data processing fixed-platform nonline-of-sight channels indoor experiments precoding matrices transceiver test bed extended channel matrices MIMO-OFDM system MIMO size SNR region 8PSK QPSK quadrature phase shift keying two-step algorithm computational complexity precoder matrix finite-alphabet inputs two-step optimal precoder design algorithm MIMO OFDM systems low complexity precoding method frequency division multiplexing experiment validation finite alphabet multiple-input multiple-output orthogonal linear precoder design

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MODIFIED algorithm FOR STEADY-STATE INTEGRATED SYSTEM OPTIMIZATION AND PARAMETER-ESTIMATION

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IEE PROCEEDINGS-D CONTROL THEORY AND APPLICATIONS 1988年第2期135卷 119-126页

作者： LIN, J CHEN, S ROBERTS, PD Control Engineering Centre City University London UK

The paper proposes an alternative modified two-step algorithm for steady state optimisation and parameter estimation. The aim is to simplify the model optimisation computation in the presence of general inequality constraints. Another advantage is that the existence of a model based optimal solution is ensured during the course of iteration. Optimality properties and convergence conditions are investigated. A simulation study is presented.

关键词： optimisation Simulation, modelling and identification general inequality constraints iterative methods Optimisation techniques iteration Interpolation and function approximation (numerical analysis) parameter estimation model based optimal solution steady state optimisation two-step algorithm

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two-step fringe pattern analysis with a Gabor filter bank

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OPTICS AND LASERS IN ENGINEERING 2016年第Oct.期85卷 29-37页

作者： Rivera, Mariano Dalmau, Oscar Gonzalez, Adonai Hernandez-Lopez, Francisco Ctr Invest Matemat AC Guanajuato 36240 Gto Mexico Univ Iberoamericana Leon Dept Ciencias & Ingn Leon 37238 Gto Mexico

We propose a two-shot fringe analysis method for Fringe Patterns (FPs) with random phase-shift and changes in illumination components. These conditions reduce the acquisition time and simplify the experimental setup. Our method builds upon a Gabor Filter (GF) bank that eliminates noise and estimates the phase from the FPs. The GF bank allows us to obtain two phase maps with a sign ambiguity between them. Due to the fact that the random sign map is common to both computed phases, we can correct the sign ambiguity. We estimate a local phase-shift from the absolute wrapped residual between the estimated phases. Next, we robustly compute the global phase-shift. In order to unwrap the phase, we propose a robust procedure that interpolates unreliable phase regions obtained after applying the GF bank. We present numerical experiments that demonstrate the performance of our method. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Fringe analysis two-step algorithm Phase measurement Phase unwrapping Gabor filters

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Robust adversarial examples against scale transformation via generative network

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ELECTRONICS LETTERS 2022年第7期58卷 290-292页

作者： Liu, Minjie Zhang, Xinpeng Feng, Guorui Shanghai Univ Sch Commun & Informat Engn Shanghai 200444 Peoples R China

Nowadays, adversarial examples of images which are generated by adding special perturbations on their hosts make great impact on many deep neural network (DNN)-based computer vision tasks and bring security risks. With the deep insight into this field, researchers realize that many simple image processing methods can easily reduce the attack success rate. Therefore, studies on robust adversarial examples that are able to defend destruction become the emphasis. However, most existing methods focus more on the distortion in user transmitting procedures and physical deformation such as JPEG compression and brightness. Given that scale transformation is one of the commonest measures in data transformation and enhancement, a two-step algorithm is proposed to eliminate the effect caused by resizing during the model inferring process. The first step is to select pixels that can affect the classification result through a DNN. As a binary classification task, the network predicts whether the pixel deserves to be modified or not. The second one is to strategically compute the amplitude of noise and add it to the host image. Experiments verify that this method resists the scale transformation and guarantees the invisibility of humans as well.

关键词： transforms image processing scale transformation image enhancement data enhancement security risks deep learning (artificial intelligence) computer crime binary classification task deep neural network-based computer vision tasks data transformation DNN-based computer vision tasks generative network robust adversarial examples two-step algorithm computer vision attack success rate reduction image classification

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