Currently, we are entering the wearable internet era. The use of WiFi signals to perceive human activities or changes in vital signs has gradually become a topic that people are enthusiastic about. Principal Component...
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ISBN:
(纸本)9798350330991;9798350331004
Currently, we are entering the wearable internet era. The use of WiFi signals to perceive human activities or changes in vital signs has gradually become a topic that people are enthusiastic about. Principal Component Analysis (PCA), as a universal data dimensionality reduction algorithm, has been widely applied in the field ofWiFi sensing. It is utilized to expedite data processing time and enhance real-time detection capabilities. This paper proposes an acceleration algorithm for PCA in the field of WiFi sensing along with its corresponding hardware architecture. The experimental results indicate that the accuracy of this algorithm can reach 0.9965, and the processing time is approximately 10 ms. Based on the TSMC 22nm technology, the Design Complier (DC) results show that the data throughput of this hardware architecture can reach 24 Gbps@800M, with a gate count of 7571, and the power consumption is 1.6321mW.
Sparse polynomial chaos expansion (PCE) can be used to emulate the stochastic model output where the original model is computationally expensive. It is a powerful tool in efficient uncertainty quantification and sensi...
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Sparse polynomial chaos expansion (PCE) can be used to emulate the stochastic model output where the original model is computationally expensive. It is a powerful tool in efficient uncertainty quantification and sensitivity analysis. Structural systems are usually associated with high dimensional and probabilistic input. The number of candidate basis functions increases significantly with input dimension, resulting in high computational burden for establishing sparse PCE. In this study, acceleration techniques are integrated to formulate an algorithm for efficient computation of sparse PCE (ASPCE). The integrated algorithm can improve efficiency of computational process compared with conventional greedy algorithm while ensuring the satisfying predictive performance. Once the sparse PCE model is obtained, the statistic moments, probability density function of stochastic output, and global sensitivity index could be computed efficiently. Traditional PCE based global sensitivity analysis only assesses the sensitivity on individual structural performance criterion. Assessing the global sensitivity considering multiple criteria is challenging as the sensitive parameters may not be consistent for different performance criteria. To address this issue, a two-stage multi-criteria global sensitivity analysis algorithm is proposed by coupling ASPCE and the technique for order preference by similarity to ideal solution (TOPSIS). A holistic global sensitivity index is proposed to identify the sensitive parameters incorporating multiple performance criteria. In order to illustrate the efficiency, accuracy, and applicability of the proposed approach, two illustrative cases are presented.
Ray tracing is an efficient channel modeling method. However, the traditional ray tracing method has high computation complexity. To solve this problem, an improved bounding volume hierarchies (BVH) algorithm is propo...
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ISBN:
(纸本)9781665454681
Ray tracing is an efficient channel modeling method. However, the traditional ray tracing method has high computation complexity. To solve this problem, an improved bounding volume hierarchies (BVH) algorithm is proposed in this paper. Based on surface area heuristic (SAH) and spatial distance, the proposed algorithm can effectively reduce the number of unnecessary intersection tests between ray and triangular facets. In addition, the algorithm fully considers the influence of ray action range, which can not only make up for the defects of spatial division based on uniform grid method and k-dimensional (KD) tree, but also solve the problem of unsatisfactory spatial division based on traditional BVH algorithm. The simulation results show that compared with the traditional BVH algorithm, the proposed algorithm can improve the computation efficiency by 20% to 35% while ensuring the computation accuracy.
The distribution system restoration (DSR) problem is traditionally modeled as a mixed-integer linear programming (MILP) model. However, a significant number of integer variables are introduced to describe the DSR proc...
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The distribution system restoration (DSR) problem is traditionally modeled as a mixed-integer linear programming (MILP) model. However, a significant number of integer variables are introduced to describe the DSR process, which introduce additional complexities in both time and space dimensions. Moreover, an enormous number of constraints are constructed to establish a rational DSR decision, while some of them may not be considered tight in practice. The enormous number of binary variables and inactive constraints could make the DSR problem very hard to solve and apply in real-time. The DSR computation burden would be reduced significantly if binary variables and binding constraints are pre-determined. This paper proposes an acceleration framework and solution algorithm based on the end-to-end optimization, which applies deep neural network (DNN) and gradient boosting decision tree (GBDT) methods to DSR. The DSR problem, which is solved in offline and online stages, will accordingly be reduced to a linear programming problem which can be solved more efficiently and reliably. Case studies are carried out on the modified IEEE 33-bus and 123-bus systems and a practical 1069-bus system. The proposed results indicate that the DSR problem with the proposed end-to-end acceleration framework is solved more than tenfold faster than those of traditional solvers.
Generally speaking, the intersection point between the ray and the terrain can be judged in the simulation software adopting the method of ray tracing, and then where the ray is intersected, reflected or diffracted wi...
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ISBN:
(纸本)9781467394451
Generally speaking, the intersection point between the ray and the terrain can be judged in the simulation software adopting the method of ray tracing, and then where the ray is intersected, reflected or diffracted with the specific terrain can be judged. At present, most terrains are simulated in the form of triangular facet, while the judgment process for one time of intersection between one ray with all triangular facets of a large terrain is relatively long. In this paper, the ray path can be estimated during the process of judging the intersection and confirming the position of the intersection point as per the ray and the terrain, the intersection judgment can be reduced, it can be accelerated, and consequently the time for ray tracing is largely shortened and the efficiency of the software simulation can be improved.
In order to improve the spectral resource utilization, the sea electromagnetic energy distribution prediction algorithm is proposed, which is the basic study of spectrum interference and offshore communication channel...
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In order to improve the spectral resource utilization, the sea electromagnetic energy distribution prediction algorithm is proposed, which is the basic study of spectrum interference and offshore communication channels. This letter studies the acceleration of the prediction algorithm for offshore electromagnetic energy distribution. In conjunction with the Pierson-Moscowitz (PM) wave spectrum, the effective rays are discretized by establishing the normal vector matrix of the reflection plane. We propose to introduce the effective reflecting surface of the PM wave spectrum to improve the estimation accuracy of the electromagnetic spectrum distribution in the complex marine environment. We provided an effective ray decision algorithm to accelerate the prediction of reflected ray field strength distribution. In particular, combining the free-space propagation loss characteristics of electromagnetic waves, ray distribution with uneven Angle Variation is proposed. Based on the PM wave spectrum, atmospheric refraction, and earth curvature of the complex marine environment model, the ray-tracing method can quickly calculate the marine electromagnetic spectrum distribution.
Generally speaking,the intersection point between the ray and the terrain can be judged in the simulation software adopting the method of ray tracing,and then where the ray is intersected,reflected or diffracted with ...
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Generally speaking,the intersection point between the ray and the terrain can be judged in the simulation software adopting the method of ray tracing,and then where the ray is intersected,reflected or diffracted with the specific terrain can be *** present,most terrains are simulated in the form of triangular facet,while the judgment process for one time of intersection between one ray with all triangular facets of a large terrain is relatively *** this paper,the ray path can be estimated during the process of judging the intersection and confirming the position of the intersection point as per the ray and the terrain,the intersection judgment can be reduced,it can be accelerated,and consequently the time for ray tracing is largely shortened and the efficiency of the software simulation can be improved.
Sobel is one of the most popular edge detection operators used in image processing. To date, most users utilize the two-directional 3x3 Sobel operator as detectors because of its low computational cost and reasonable ...
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Sobel is one of the most popular edge detection operators used in image processing. To date, most users utilize the two-directional 3x3 Sobel operator as detectors because of its low computational cost and reasonable performance. Simultaneously, many studies have been conducted on using large multi-directional Sobel operators to satisfy their needs considering the high stability, but at an expense of speed. This paper proposes a fast graphics processing unit (GPU) kernel for the four-directional 5x5 Sobel operator. To improve kernel performance, we implement the kernel based on warp-level primitives, which can significantly reduce the number of memory accesses. In addition, we introduce the prefetching mechanism and operator transformation into the kernel to significantly reduce the computational complexity and data transmission latency. Compared with the OpenCV-GPU library, our kernel shows high performances of 6.7x speedup on a Jetson AGX Xavier GPU and 13x on a GTX 1650Ti GPU. (C) 2023 Elsevier Inc. All rights reserved.
In this work, we theoretically and numerically discuss a class of time fractional normal-subdiffusion transport equation, which depicts a crossover from normal diffusion (as t -> 0) to sub-diffusion (as t -> inf...
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In this work, we theoretically and numerically discuss a class of time fractional normal-subdiffusion transport equation, which depicts a crossover from normal diffusion (as t -> 0) to sub-diffusion (as t -> infinity). Firstly, the well-posedness and regularities of the model are studied by using the bivariate Mittag-Leffler function. Theoretical results show that after introducing the first-order derivative operator, the regularity of the solution can be improved in substance. Then, a numerical scheme with high-precision is developed nomatter the initial value is smooth or non-smooth. More specifically, we use the contour integral method (CIM) with parameterized hyperbolic contour to approximate the temporal local and non-local operators, and employ the standard Galerkin finite element method for spatial discretization. Rigorous error estimates show that the proposed numerical scheme has spectral accuracy in time and optimal convergence order in space. Besides, we further improve the algorithm and reduce the computational cost by using the barycentric Lagrange interpolation. Finally, the obtained theoretical results as well as the acceleration algorithm are verified by several 1-D and 2-D numerical experiments, which also show that the numerical scheme developed in this paper is effective and robust.
A parallel Jacobian-Free Newton Krylov discrete ordinates method (comePSn_JFNK) is proposed to solve the multi-dimensional multi-group pin-by-pin neutron transport models, which makes full use of the good efficiency a...
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A parallel Jacobian-Free Newton Krylov discrete ordinates method (comePSn_JFNK) is proposed to solve the multi-dimensional multi-group pin-by-pin neutron transport models, which makes full use of the good efficiency and parallel performance of the JFNK framework and the high accuracy of the Sn method for the large-scale models. In this paper, the k-eigenvalue and the scalar fluxes (rather than the angular fluxes) are chosen as the global solution variables of the parallel JFNK method, and the corresponding residual functions are evaluated by the Koch-Baker-Alcouffe (KBA) algorithm with the spatial domain decomposition in the parallel Sn framework. Unlike the original Sn iterative strategy, only a "flattened " power iterative process which includes a single outer iteration without nested inner iterations is required for the JFNK strategy. Finally, the comePSn_JFNK code is developed in C++ language and, the numerical solutions of the 2-D/3-D KAIST-3A benchmark problems and the 2-D/3-D full-core MOX/UOX pin-by-pin models with different control rod distribution show that comePSn_JFNK method can obtain significant efficiency advantage compared with the original power iteration method (comePSn) for the parallel simulation of the large-scale complicated pin-by-pin models.
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