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The improvement of the performance of online separating speech and music is an NP problem and the separation optimization increases the complexity of the method in a Robust Principal Component Analysis (RPCA) method which is time consuming in big size matrix computations. This paper presents a RPCA-based speech and music separation method to reduce the amount of computational complexity and be robust to artificial noise by proposing two novel algorithms. The key idea of our real-time method is designing a novel random singular value decomposition algorithm in a non-convex optimization environment to significantly decrease the complexity of previous RPCA methods from min(mn2,m2n) flops to mnr flops where r≪min(m,n) to obtain better performance and get qualified results. Experimental results of different datasets compared with the best state-of-the-art method show that the proposed method is more reliable and achieves an average 339% speedup by the significant reduction of computational complexity, increases the quality of the speech signal by 295%, improves the quality of the music signal by 244% and the robustness of artificial noise without needing any learning technique or requiring particular features.
Mohaddeseh Mirbeygi; Aminollah Mahabadi; Akbar Ranjbar. RPCA-based real-time speech and music separation method. Speech Communication 2020, 126, 22 -34.
AMA StyleMohaddeseh Mirbeygi, Aminollah Mahabadi, Akbar Ranjbar. RPCA-based real-time speech and music separation method. Speech Communication. 2020; 126 ():22-34.
Chicago/Turabian StyleMohaddeseh Mirbeygi; Aminollah Mahabadi; Akbar Ranjbar. 2020. "RPCA-based real-time speech and music separation method." Speech Communication 126, no. : 22-34.
Performance improvement of community detection is an NP problem in large social networks analysis where by integrating the overlapped communities’ information and modularity maximization increases the time complexity and memory usage. This paper presents an online parallel overlapping community detection approach based on a speaker-listener propagation algorithm by proposing a novel parallel algorithm and applying three new metrics. This approach is presented to improve modularity and expand scalability for getting a significantly speedup in low time-consuming and usage memory through an agent-based parallel implementation in a multi-core architecture. The key ideas of our approach are increasing the communities’ conductance score, limiting the speaking-listening stages and executing a strategic updating order to develop a speaker-listeners label propagation algorithm for getting better speedup and semi-deterministic results without using prior training or requiring particular predefined features. Experimental results of used large datasets compared with state-of-the-art algorithms show that the proposed method is extremely convergence and achieves an average 820% speedup in the label propagation algorithm, and significantly improves the modularity that are effective in finding better overlapping communities in a linear time complexity O(m) and lower usage memory O(n).
Aminollah Mahabadi; Mohammad Hosseini. SLPA-based parallel overlapping community detection approach in large complex social networks. Multimedia Tools and Applications 2020, 80, 6567 -6598.
AMA StyleAminollah Mahabadi, Mohammad Hosseini. SLPA-based parallel overlapping community detection approach in large complex social networks. Multimedia Tools and Applications. 2020; 80 (5):6567-6598.
Chicago/Turabian StyleAminollah Mahabadi; Mohammad Hosseini. 2020. "SLPA-based parallel overlapping community detection approach in large complex social networks." Multimedia Tools and Applications 80, no. 5: 6567-6598.
As advanced Smart Grid environments grow from a simple grid towards a complex provider ecosystem, there is an uncertain challenge on those grid environments that need to manage a risk paradigm. We present an automated risk-aware service level agreements modeling to the grid provider for speed automated pricing and getting better performance to program as an agent-oriented platform. The key idea of our novel approach is proposing a risk level agreements contract and a pricing model to decrease the complexity of previous methods from an off-line service level agreement to an on-line risk level agreement for managing the risk lifecycle of contracts used to record the rights and obligations of the services and their consumers. Based on a risk level agreements contract the model optimizes resource management according to the business objective level of the provider with an online risk-aware rendezvous to define the penalty level of the cost model. The corresponding quality of service criteria is defined based on multi-class risk-aware service level agreements between Smart Grid providers and their power consumers which include the tail distributions of the per-class costs in addition to the more standard quality of service metrics such as throughput and mean delays. Our empirical experiments show the benefits of the proposed approach.
Aminollah Mahabadi; Mohammad Reza Besmi. Risk-aware service level agreement modeling in smart grid. Multimedia Tools and Applications 2020, 80, 1433 -1456.
AMA StyleAminollah Mahabadi, Mohammad Reza Besmi. Risk-aware service level agreement modeling in smart grid. Multimedia Tools and Applications. 2020; 80 (1):1433-1456.
Chicago/Turabian StyleAminollah Mahabadi; Mohammad Reza Besmi. 2020. "Risk-aware service level agreement modeling in smart grid." Multimedia Tools and Applications 80, no. 1: 1433-1456.
Development of renewable energies and DC loads have led microgrids toward the creation of DC networks. The predictions show that the hybrid microgrids will be used widely in the future. This article has studied the voltage stability in the presence of sources of energy storage in AC/DC hybrid networks. However, because the different dynamics of hybrid networks applying centralized and distributed controllers will be faced with different problems, in this study, a multi-agent control for the microgrid has been used. A new structure referred to here as an event-driven microgrid control management (EDMCM) has been developed to control the microgrid. This method increases response speed and accuracy of decision making. Hybrid Network Simulation results confirm the validity of the developed model.
Ahmadali Khatibzadeh; Mohammadreza Besmi; Aminollah Mahabadi; Mahmoud Reza Haghifam. Multi-Agent-Based Controller for Voltage Enhancement in AC/DC Hybrid Microgrid Using Energy Storages. Energies 2017, 10, 169 .
AMA StyleAhmadali Khatibzadeh, Mohammadreza Besmi, Aminollah Mahabadi, Mahmoud Reza Haghifam. Multi-Agent-Based Controller for Voltage Enhancement in AC/DC Hybrid Microgrid Using Energy Storages. Energies. 2017; 10 (2):169.
Chicago/Turabian StyleAhmadali Khatibzadeh; Mohammadreza Besmi; Aminollah Mahabadi; Mahmoud Reza Haghifam. 2017. "Multi-Agent-Based Controller for Voltage Enhancement in AC/DC Hybrid Microgrid Using Energy Storages." Energies 10, no. 2: 169.