This paper introduces an efficient and simple algorithm for constructing Multiple Reference (MR) octrees on a GPU in application to Photon Mapping and Irradiance Caching techniques. Although MR-octrees are hierarchica...
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This paper introduces an efficient and simple algorithm for constructing Multiple Reference (MR) octrees on a GPU in application to Photon Mapping and Irradiance Caching techniques. Although MR-octrees are hierarchical structures, we successfully ignore their hierarchical nature and present an approach with plain construction, compact data layout and stack-less traversal. Our algorithm uses only 2 parallel primitives (parallel append and parallel sort) and can be expressed in several lines of pseudo-code.
A multi-scale framework is proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent. This...
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A multi-scale framework is proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent. This article reports our initial efforts to formulate the physical concepts necessary for coupling the two mechanics and develop a 3D numerical algorithm to simulate the solvent fluid via the Navier-Stokes equation. The numerical algorithm was validated with multiple test cases. The validation shows that the algorithm is effective and stable, with observed accuracy consistent with our design.
Orthogonal frequency division multiplexing (OFDM) has been widely adopted in radar and communication systems. High sensitivity to carrier frequency offset (CFO) is one of the major drawbacks of OFDM. CFO estimation fo...
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Orthogonal frequency division multiplexing (OFDM) has been widely adopted in radar and communication systems. High sensitivity to carrier frequency offset (CFO) is one of the major drawbacks of OFDM. CFO estimation for OFDM systems had been extensively studied and various algorithms had been proposed. however, the established algorithms may be compromised by the adoption of direct-conversion architecture and multi-mode low noise amplifier in the OFDM receiver, which introduces time-varying direct current offset (TV-DUO) into the system. In our previous study, we developed an eigen-decomposition based estimation algorithm, which is robust to TV-DCO but suffers from performance degradation under low to medium signal-to-noise ratio and requires high computation efforts. To address those issues, we in this paper propose a novel blind CFO estimation algorithm. By making use of the second order differential filtering and subspace method, the proposed algorithm achieves great performance improvement with reduced complexity. The performance of the proposed algorithm is demonstrated by simulations. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Vibration signals captured from faulty mechanical components are often associated with transients which are significant for machinery fault diagnosis. However, the existence of strong background noise makes the detect...
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Vibration signals captured from faulty mechanical components are often associated with transients which are significant for machinery fault diagnosis. However, the existence of strong background noise makes the detection of transients a basis pursuit denoising (BPD) problem, which is hard to be solved in explicit form. With sparse representation theory, this paper proposes a novel method for machinery fault diagnosis by combining the wavelet basis and majorization-minimization (MM) algorithm. This method converts transients hidden in the noisy signal into sparse coefficients;thus the transients can be detected sparsely. Simulated study concerning cyclic transient signals with different signal-to-noise ratio (SNR) shows that the effectiveness of this method. The comparison in the simulated study shows that the proposed method outperforms the method based on split augmented Lagrangian shrinkage algorithm (SALSA) in convergence and detection effect. Application in defective gearbox fault diagnosis shows the fault feature of gearbox can be sparsely and effectively detected. A further comparison between this method and the method based on SALSA shows the superiority of the proposed method in machinery fault diagnosis.
The presented paper aims to analyze the influence of the selection of transfer function and training algorithms on neural network flood runoff forecast. Nine of the most significant flood events, caused by the extreme...
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The presented paper aims to analyze the influence of the selection of transfer function and training algorithms on neural network flood runoff forecast. Nine of the most significant flood events, caused by the extreme rainfall, were selected from 10 years of measurement on small headwater catchment in the Czech Republic, and flood runoff forecast was investigated using the extensive set of multilayer perceptrons with one hidden layer of neurons. The analyzed artificial neural network models with 11 different activation functions in hidden layer were trained using 7 local optimization algorithms. The results show that the Levenberg-Marquardt algorithm was superior compared to the remaining tested local optimization methods. When comparing the 11 nonlinear transfer functions, used in hidden layer neurons, the RootSig function was superior compared to the rest of analyzed activation functions.
Focusing on novel database application scenarios, where data sets arise more and more in uncertain and imprecise formats, in this paper we propose a novel decomposition framework for efficiently computing and querying...
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Focusing on novel database application scenarios, where data sets arise more and more in uncertain and imprecise formats, in this paper we propose a novel decomposition framework for efficiently computing and querying multidimensional OLAP data cubes over probabilistic data, which well-capture previous kind of data. Several models and algorithms supported in our proposed framework are formally presented and described in details, based on well-understood theoretical statistical/probabilistic tools, which converge to the definition of the so-called probabilistic OLAP data cubes, the most prominent result of our research. Finally, we complete our analytical contribution by introducing an innovative Probability Distribution Function (PDF)-based approach, which makes use of well-known probabilistic estimators theory, for efficiently querying probabilistic OLAP data cubes, along with a comprehensive experimental assessment and analysis over synthetic probabilistic databases.
The relationship between structural controllability and observability of complex systems is studied. Algebraic and graph theoretic tools are combined to prove the extent of some controller/observer duality results. Tw...
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The relationship between structural controllability and observability of complex systems is studied. Algebraic and graph theoretic tools are combined to prove the extent of some controller/observer duality results. Two types of control design problems are addressed and some fundamental theoretical results are provided. In addition new algorithms are presented to compute optimal solutions for monitoring large scale real networks.
One of the most common defects in digital photography is motion blur caused by camera shake. Shift-invariant motion blur can be modeled as a convolution of the true latent image and a point spread function (PSF) with ...
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One of the most common defects in digital photography is motion blur caused by camera shake. Shift-invariant motion blur can be modeled as a convolution of the true latent image and a point spread function (PSF) with additive noise. The goal of image deconvolution is to reconstruct a latent image from a degraded image. However, ringing is inevitable artifacts arising in the deconvolution stage. To suppress undesirable artifacts, regularization based methods have been proposed using natural image priors to overcome the ill-posedness of deconvolution problem. When the estimated PSF is erroneous to some extent or the PSF size is large, conventional regularization to reduce ringing would lead to loss of image details. This paper focuses on the nonblind deconvolution by adaptive regularization which preserves image details, while suppressing ringing artifacts. The way is to control the regularization weight adaptively according to the image local characteristics. We adopt elaborated reference maps that indicate the edge strength so that textured and smooth regions can be distinguished. Then we impose an appropriate constraint on the optimization process. The experiments' results on both synthesized and real images show that our method can restore latent image with much fewer ringing and favors the sharp edges.
To express temporal properties of dense-time real-valued signals, the Signal Temporal Logic (STL) has been defined by Maler et al. The work presented a monitoring algorithm deciding the satisfiability of STL formulae ...
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To express temporal properties of dense-time real-valued signals, the Signal Temporal Logic (STL) has been defined by Maler et al. The work presented a monitoring algorithm deciding the satisfiability of STL formulae on finite discrete samples of continuous signals. The logic is not expressive enough to sufficiently distinguish oscillatory properties important in biology. In this paper we introduce the extended logic STL* in which STL is augmented with a signal-value freezing operator allowing to express (and distinguish) various dynamic aspects of oscillations. This operator may be nested for further increase of expressiveness. The logic is supported by a monitoring algorithm prototyped in Matlab for the fragment that avoids nesting of the freezing operator. The monitoring procedure for STL* is evaluated on a sample oscillatory signal with varied parameters. Application of the extended logic is demonstrated on a case study of a biological oscillator. We also discuss expressive power of STL with respect to STL*. (c) 2014 Elsevier Inc. All rights reserved.
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