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A Study on QoS of VoIP networks: A Random Neural Network (RNN) Approach

机译:VoIP网络的QoS研究:随机神经网络(RNN)方法

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Voice over Internet Protocol (VoIP) is predicted to be the replacement of the traditional PSTN telephone system. Quality of Service (QoS) of VoIP systems are more difficult to measure and implement compared to PSTN systems. The nature of QoS in VoIP networks is very variable and hence it is important to be able to measure the QoS offered by the system in real time with a low computational cost. So it is very important to measure the quality of service offered by VoIP networks. In this paper we discuss a new novel model to calculate the perceived voice quality using Random Neural Network (RNN). The RNN is an open Markovian queuing model, motivated by spiking behaviour of biological neurons that has been used for several applications. We used the feedforward architecture with different numbers of hidden neurons to test the stability of our model. We study the RNN model with 4, 5, and 6 hidden layers of neurons. Our model shows a high degree of accuracy
机译:预计互联网协议语音(VoIP)将取代传统的PSTN电话系统。与PSTN系统相比,VoIP系统的服务质量(QoS)更加难以衡量和实现。 VoIP网络中QoS的性质变化很大,因此重要的是能够以低计算成本实时测量系统提供的QoS。因此,衡量VoIP网络提供的服务质量非常重要。在本文中,我们讨论了一种使用随机神经网络(RNN)计算感知语音质量的新型模型。 RNN是一种开放的马尔可夫排队模型,其受生物神经元的尖峰行为所激发,该行为已用于多种应用。我们使用具有不同数量的隐藏神经元的前馈架构来测试模型的稳定性。我们研究了具有4、5和6个神经元隐藏层的RNN模型。我们的模型显示出很高的准确性

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