Overlay multicast has become one of the most promising multicast solutions for IP network,and Neutral Network(NN) has been a good candidate for searching optimal solutions to the constrained shortest routing path in v...Overlay multicast has become one of the most promising multicast solutions for IP network,and Neutral Network(NN) has been a good candidate for searching optimal solutions to the constrained shortest routing path in virtue of its powerful capacity for parallel computation. Though traditional Hopfield NN can tackle the optimization problem,it is incapable of dealing with large scale networks due to the large number of neurons. In this paper,a neural network for overlay multicast tree com-putation is presented to reliably implement routing algorithm in real time. The neural network is constructed as a two-layer recurrent architecture,which is comprised of Independent Variable Neurons(IDVN) and Dependent Variable Neurons(DVN) ,according to the independence of the decision variables associated with the edges in directed graph. Compared with the heuristic routing algorithms,it is characterized as shorter computational time,fewer neurons,and better precision.展开更多
Abstract： A hierarchical method for scene analysis in audio sensor networks is proposed. This meth-od consists of two stages： element detection stage and audio scene analysis stage. In the former stage, the basic au...Abstract： A hierarchical method for scene analysis in audio sensor networks is proposed. This meth-od consists of two stages： element detection stage and audio scene analysis stage. In the former stage, the basic audio elements are modeled by the HMM models and trained by enough samples off-line, and we adaptively add or remove basic ele- ment from the targeted element pool according to the time, place and other environment parameters. In the latter stage, a data fusion algorithm is used to combine the sensory information of the same ar-ea, and then, a role-based method is employed to analyze the audio scene based on the fused data. We conduct some experiments to evaluate the per-formance of the proposed method that about 70% audio scenes can be detected correctly by this method. The experiment evaluations demonstrate that our method can achieve satisfactory results.展开更多
基金the High-tech Project of Jiangsu Province (No.BG2003001).
文摘Overlay multicast has become one of the most promising multicast solutions for IP network,and Neutral Network(NN) has been a good candidate for searching optimal solutions to the constrained shortest routing path in virtue of its powerful capacity for parallel computation. Though traditional Hopfield NN can tackle the optimization problem,it is incapable of dealing with large scale networks due to the large number of neurons. In this paper,a neural network for overlay multicast tree com-putation is presented to reliably implement routing algorithm in real time. The neural network is constructed as a two-layer recurrent architecture,which is comprised of Independent Variable Neurons(IDVN) and Dependent Variable Neurons(DVN) ,according to the independence of the decision variables associated with the edges in directed graph. Compared with the heuristic routing algorithms,it is characterized as shorter computational time,fewer neurons,and better precision.
基金This work was supported by the Projects of the National Nat-ura! Science Foundation of China under Crant No.U0835001 the Fundamental Research Funds for the Central Universities-2011PTB-00-28.
文摘Abstract： A hierarchical method for scene analysis in audio sensor networks is proposed. This meth-od consists of two stages： element detection stage and audio scene analysis stage. In the former stage, the basic audio elements are modeled by the HMM models and trained by enough samples off-line, and we adaptively add or remove basic ele- ment from the targeted element pool according to the time, place and other environment parameters. In the latter stage, a data fusion algorithm is used to combine the sensory information of the same ar-ea, and then, a role-based method is employed to analyze the audio scene based on the fused data. We conduct some experiments to evaluate the per-formance of the proposed method that about 70% audio scenes can be detected correctly by this method. The experiment evaluations demonstrate that our method can achieve satisfactory results.
