In this letter, we present an iterative algorithm for constructing high-dimensional incoherent Grassmannian Frames (GFs) which are sets of unit-norm vectors that are minimax optimal: the maximum absolute value of thei...
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In this letter, we present an iterative algorithm for constructing high-dimensional incoherent Grassmannian Frames (GFs) which are sets of unit-norm vectors that are minimax optimal: the maximum absolute value of their inner products is a minimum. We formulate the GF design as a nonconvex optimization problem and solve it via an efficient iterative algorithm. The bulk of each iteration of the proposed algorithm is a linear Program (LP) for which there are a host of efficient solvers. The proposed algorithm is based on the theoretically sound Minorization Maximization technique which, unlike some of the state-of-the-art design approaches, monotonically minimizes the design criterion and can construct GFs with low coherence values.
In & x201C;Shared Manufacturing & x201D;environment, orders are processed in a given job sequence which is based on the time of receipt of orders. This paper studies a problem of scheduling two-task jobs in a ...
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In & x201C;Shared Manufacturing & x201D;environment, orders are processed in a given job sequence which is based on the time of receipt of orders. This paper studies a problem of scheduling two-task jobs in a two-machine hybrid flow-shop subject to a given job sequence which is used in production of electronic circuits under shared manufacturing. Each job has two tasks: the first one is a flexible task, which can be processed on either of the two machines, and the second one is a preassigned task, which can only be processed on the second machine after the first task is finished. Each job has a processing deadline. Three objective functions related to deadlines are considered. The computational complexity of the problem for any of three objective functions is showed to be ordinary NP-hard, a dynamic programming algorithm (DPA) is presented for each case and the time complexity of each algorithm is given. The results of computational experiments show the relationship between the running time of DPA and the parameters, and also show the advantages of DPA in dealing with this problem compared with branch-and-bound algorithm and iterated greedy algorithm.
In this paper, we propose a new beamforming design for intelligent reflecting surface (IRS) assisted multi-user systems where a base station with multiple antennas support several users with an aid of an IRS. We joint...
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In this paper, we propose a new beamforming design for intelligent reflecting surface (IRS) assisted multi-user systems where a base station with multiple antennas support several users with an aid of an IRS. We jointly optimize the sum rate and the user fairness by adopting a single objective function. To tackle the non-convex problem, we present an iterative algorithm based on the successive convex approximation method. Simulation results demonstrate that the proposed scheme outperforms other conventional IRS based schemes in terms of both the sum-rate and user fairness.
Robust look-ahead dispatch (RLAD) is essential to manage uncertainties in power systems. As its key step, the worst-case scenario identification (WCSI) problem is cast to a max-min program. This computationally intens...
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Robust look-ahead dispatch (RLAD) is essential to manage uncertainties in power systems. As its key step, the worst-case scenario identification (WCSI) problem is cast to a max-min program. This computationally intensive procedure has to be performed repeatedly, impairing the computational efficiency of RLAD. To address this issue, an efficient RLAD scheme incorporating critical region preparation in gap time is proposed. The computation burden is mostly transferred from the online decision stage to the gap time via a customized technique based on multi-parametric programming. The accuracy of computing the critical regions is validated by the test in a six-bus system, and the proposed method is shown to cut down 21% of total iterations and save computational time dramatically by the test in a practical-scale system in Northeastern China.
Attributed network embedding (ANE) is to learn low-dimensional vectors so that not only the network structure but also node attributes can be preserved in embeddings. Existing ANE models do not consider the specific c...
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ISBN:
(数字)9781665408837
ISBN:
(纸本)9781665408837
Attributed network embedding (ANE) is to learn low-dimensional vectors so that not only the network structure but also node attributes can be preserved in embeddings. Existing ANE models do not consider the specific combination between graph structure and attributes. While each node has its structural characteristics, such as highly-interconnected neighbors along with their certain patterns of attribute distribution, each node's neighborhood should be not only depicted by multi-hop nodes, but consider certain social circles. To model such information, in this paper, we propose a novel ANE model, Context Cooccurrence-aware Attributed Network Embedding (CoANE). The basic idea of CoANE is to model the context attributes for each node, and apply the convolutional mechanism to encode latent social circles. To better preserve network knowledge, we devise objective functions including positive graph likelihood, contextual negative sampling, and attribute reconstruction. We conduct experiments on five real datasets for downstream tasks, including node classification, link prediction, and community detection. The results exhibit that CoANE can significantly outperform state-ofthe-art ANE models. This work was accepted to IEEE TKDE
Workplaces that mostly rely on part-time workers, such as product manufacturing lines and factories, limit the working hours of their employees. Therefore, work scheduling is a very important task in project managemen...
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In this letter, a novel weighted mean square error (WMSE) is proposed to improve the DNN-based mask approximation method for speech enhancement, in which the weighting is closely related to the power exponent about no...
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In this letter, a novel weighted mean square error (WMSE) is proposed to improve the DNN-based mask approximation method for speech enhancement, in which the weighting is closely related to the power exponent about noisy spectrum amplitude (NSA) base. The power exponents 0 and 2 separately reflect ideal amplitude masking (IAM) without any clippings and the indirect mapping (IM) on short-time spectral amplitude (STSA), and it is highly related to the enhanced spectrum and the performance of the enhanced signal based on the tests. Also, the experimental results show that the outstanding weighting is the noisy spectrum base with the power exponent 1 for the phase-unaware masking and results in better harmonic structure restoration. The objective function with the WMSE on the NSA (WMSE-NSA) can averagely improve 0.1 on the test of perceptual evaluation of speech quality (PESQ) and 1.7% on the test of short-time objective intelligibility (STOI) compared with the MSE-based mask approximation methods.
The Link-a-Pix puzzle, which is also known as Piczle, PathPix, Pictlink, Number Net, or Paint by Pairs, is a popular picture logic puzzle game where the player paints a grid by linking the hint points with number-colo...
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The Link-a-Pix puzzle, which is also known as Piczle, PathPix, Pictlink, Number Net, or Paint by Pairs, is a popular picture logic puzzle game where the player paints a grid by linking the hint points with number-color labels to obtain the solution as a pixel art picture. In this article, we propose a joint depth first searching and linear programming aided algorithm for the sake of automatically solving the Link-a-Pix puzzle. The experiments implemented on 40 puzzles with various types verify the effectiveness and feasibility of our proposed solver, which is conducive to both designing and solving the Link-a-Pix puzzles and related applications.
We consider the problem of transforming a coherent lower probability into another one that (i) belongs to some subclass with better mathematical properties, such as 2- or complete monotonicity;(ii) is at least as info...
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The startup of systems composed of power electronic systems is becoming more complex. As the systems grow, standard pre-configuration sequencing methods will struggle. This work proposes a linear programming optimizat...
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