Based on a new similarity model for the voice excitation process, a novel pitch determination procedure is derived. The unique features of the proposed algorithm are infinite (super) resolution, better accuracy than t...
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Based on a new similarity model for the voice excitation process, a novel pitch determination procedure is derived. The unique features of the proposed algorithm are infinite (super) resolution, better accuracy than the difference limen for F(o), robustness to noise, reliability, and modest computational complexity. The algorithm is instrumental to speech processing applications which require pitch synchronous spectral analysis.
Object detection plays a critical role for automatic video analysis in many vision applications. Background subtraction has been the mainstream in the field of moving objects detection. However, most of state-of-the-a...
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Object detection plays a critical role for automatic video analysis in many vision applications. Background subtraction has been the mainstream in the field of moving objects detection. However, most of state-of-the-art techniques of background subtraction operate on each pixel independently ignoring the global features of images. A motion detection method based on subspace update of background is proposed in this study. This method uses a subspace spanned by the principal components of background sequence to characterise the background and integrates the regional continuity of objects to segment the foreground. To deal with changes in the background geometry, a learning factor is introduced into the authors' model to update the subspace timely. Additionally, to reduce computational complexity, they use two-dimension principal component analysis (PCA) rather than traditional PCA to obtain the principal components of background. Experiments demonstrate that the update policy is effective and in most cases this proposed method can achieve better results than others compared in this study.
The packing chromatic number chi(p)(G) of a graph G is the smallest integer k such that the vertex set of G can be partitioned into packings with pairwise different widths. Several lower and upper bounds are obtained ...
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The packing chromatic number chi(p)(G) of a graph G is the smallest integer k such that the vertex set of G can be partitioned into packings with pairwise different widths. Several lower and upper bounds are obtained for the packing chromatic number of Cartesian products of graphs. It is proved that the packing chromatic number of the infinite hexagonal lattice lies between 6 and 8. Optimal lower and upper bounds are proved for subdivision graphs. Trees are also considered and monotone colorings are introduced. (C) 2007 Elsevier B.V. All rights reserved.
Reliable detection of primary users (PUs) in the presence of interference and noise is a crucial problem in cognitive radio networks. To address the above issue, cooperative spectrum sensing based on cyclostationary f...
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Reliable detection of primary users (PUs) in the presence of interference and noise is a crucial problem in cognitive radio networks. To address the above issue, cooperative spectrum sensing based on cyclostationary feature detection that can robustly detect weak primary signals has been proposed in the literature. Among different cooperative techniques, in this study the authors focus on combination of soft decisions derived based on asymptotic properties of cyclic autocorrelation estimates. The objective is to maximise deflection coefficient performance metric at the fusion centre, where linear combination of cyclostationary soft decisions is performed. Since the proposed method allows for distributed cyclostationarity spectrum sensing, it is more reliable and faster than non-cooperative traditional multi-cycle cyclostationarity detection schemes. To reduce the computational complexity of the exact distribution of proposed test statistic at fusion centre, the authors derive efficient approximations for the distribution under null and alternative hypotheses. Extensive simulation results in different scenarios demonstrate the advantage of the proposed method and confirm the analytic performance characterisations. In addition, the authors study the impact of mobility of cognitive devices on the cyclostationarity of received signals and verify our analysis via simulation.
In the design of software metrics, increasing attention has been given to the complexity arising from the pattern of coupling among subprograms. We call it the ''subprogram problem'' - to discover the ...
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In the design of software metrics, increasing attention has been given to the complexity arising from the pattern of coupling among subprograms. We call it the ''subprogram problem'' - to discover the most effective means whereby one might judiciously assign a measure to the subprogram calls appearing in the context of tightly-coupled modules. We phrase our solution in the language of matrix analysis, giving rise to both an exact and an iterative computational approach. The resulting methodology is uniform over a wide range of software metrics, integrating an accounting for the coupling complexity into the extended meaning of a particular metric. A running example is provided, fully illustrating the technique.
The standard agent glucose has been the subject of numerous experimental and theoretical studies, especially in the aqueous environments which are present in most biochemical processes. The impact of the solvation pro...
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The standard agent glucose has been the subject of numerous experimental and theoretical studies, especially in the aqueous environments which are present in most biochemical processes. The impact of the solvation process on the vibrational spectra of glucose in the mid-infrared region is investigated in this work. The computational study focused both on the variation of the number of surrounding water molecules from 0 to 229 and on the number of single spectra included in the iterative averaging process. The calculations consisted of a combination of force field methods for the sampling of the configuration space and density functional theory for further geometry optimizations. Effective fragment potentials (EFPs) were employed for the description of the solvent as a compromise between accuracy and computational complexity. A correlation between the experimental data and the number of surrounding water molecules could not be observed for an averaging over a small set of computed single spectra. The inclusion of an additionial polarizable continuum model (PCM) also showed no further impact. However, an increase in the number of underlying single spectra in the averaging process increased the correlation between simulations and the experiment substantially. Especially for 18 explicit EFP water molecules, an inclusion of 80 single spectra delivered a Pearson's correlation coefficient r approximate to 0.94.
The growing complexity of optimization problems in distributed systems (DSs) has motivated computer scientists to strive for efficient approaches. This paper presents a novel cooperative algorithm inspired by chaos-or...
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The growing complexity of optimization problems in distributed systems (DSs) has motivated computer scientists to strive for efficient approaches. This paper presents a novel cooperative algorithm inspired by chaos-order transition in a chaotic ant swarm (CAS). This work analyzes the basic dynamic characteristics of a DS in light of a networked multiagent system at microlevel and models a mapping from state set to self-organization mechanism set under the guide of system theory at macrolevel. A collaborative optimization algorithm(COA) in DS based on the chaos-order transition of CAS is then devised. To verify the validity of the proposed model and algorithm, we solve a locality-based task allocation in a networked multiagent system that uses COA. Simulations show that our algorithm is feasible and effective compared with previous task allocation approaches, thereby illustrating that our design ideas are correct.
In this paper we introduce the concept of Horn functions and investigate the structure of their disjunctive normal forms. Horn functions arise in a variety of applications, including in particular the analysis of prod...
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In this paper we introduce the concept of Horn functions and investigate the structure of their disjunctive normal forms. Horn functions arise in a variety of applications, including in particular the analysis of production rule knowledge bases of propositional expert systems. The goal of this paper is to reduce the study of the irredundant prime disjunctive normal forms of Horn functions to the study of the irredundant prime disjunctive normal forms of pure Horn functions. This reduction is achieved by proving that every prime irredundant disjunctive normal form of a Horn function consists of a prime irredundant disjunctive normal form of its "pure Horn component", and of a "positive restriction" of the function. We provide a constructive characterization of all the positive restrictions, and present an efficient algorithm for decomposing any Horn function into its pure Horn component and its positive restriction. Finally, we reduce in quadratic time the minimization of a Horn function to the minimization of its pure Horn component.
We demonstrate a distributed and a centralized 4G/5G compliant approach to minimize signaling and latency related to user mobility in cellular networks. This is crucial due to the densification of networks and the add...
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We demonstrate a distributed and a centralized 4G/5G compliant approach to minimize signaling and latency related to user mobility in cellular networks. This is crucial due to the densification of networks and the additional signaling introduced by the new 5G service-based architecture. By exploiting standardized protocols, our solutions dynamically reorganize the association between nodes in radio access network (RAN) and the core. We validated the proposed approaches using real user mobility datasets. Our results show that both our distributed and centralized solutions significantly reduce the signaling between core and RAN compared to the traditional approach based on geographical proximity. As a result, both approaches significantly reduce the average handover procedure processing time. Moreover, by relying on locally available information, the distributed approach can quickly adapt to changes in the user movement patterns as they happen.
The idea of explicit model predictive control (MPC) is to characterize optimal control inputs as an explicit piecewise affine (PWA) function of the initial conditions. The function, however, is often too complex and e...
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The idea of explicit model predictive control (MPC) is to characterize optimal control inputs as an explicit piecewise affine (PWA) function of the initial conditions. The function, however, is often too complex and either requires too much processing power to evaluate on-line, or consumes a prohibitive amount of memory. The paper focuses on the memory issue and proposes a novel method of replacing a generic continuous PWA function by a different function of significantly lower complexity in such a way that the simple function guarantees the same properties as the original. The idea is based on eliminating regions of the PWA function over which the function attains a saturated value. An extensive case study is presented which confirms that a significant reduction of complexity is achieved in general.
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