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When facing radar target recognition, the main problems focus on the data representation capability and the robustness to cope with noise. The merits of deep learning such as automatic setting for training and hierarchical extraction of features. Most of existing deep networks are related to Restricted Boltzmann machine (RBM), which has played an important role in deep learning techniques. The models...
This paper proposes an analytical model for dimensioning transport bandwidths in the Long Term Evolution (LTE) access network. In this work the criterion for dimensioning is the transport network delay QoS (at the packet level). The presented analytical model takes into considerations the key features of the LTE radio interface and the use of Differentiated Service (DiffServ) QoS scheme in the LTE...
This paper presents analytical models to dimension the transport bandwidths for the S1 interface in the Long Term Evolution (LTE) Network. In this paper, we consider two major traffic types: elastic traffic and real time traffic. For each type of traffic, individual dimensioning models are proposed. For validating these analytical dimensioning models, a developed LTE system simulation model is used...
This paper proposes efficient analytical models to dimension the required transport bandwidths for the Long Term Evolution (LTE) access network for the elastic Internet traffic (which is carried by the TCP protocol). The dimensioning models are based on the use of Processor Sharing queuing theory to guarantee a desired end-to-end application QoS target. For validating the analytical dimensioning models,...
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