The goal of this paper is to estimate the capital investment in telecom network’s equipments, by using Cobb-Douglas model to predict the number of subscribers for the next years of Iran. By presenting a master plan for “fixed telephony”, “mobile telephony”, “data”, “transmission”, and “access” networks, the required equipments and also the capital investment amounts […]
In this paper, the signal-to-noise ratio (SNR) of dynamic communication channels, using a radial basis function (RBF) neural network with time-delay structure, is estimated. The exactitude of the estimation is sufficient for systems which are based on link adaptation techniques. The proposed system for estimating SNR does not demand on having any prior knowledge about […]
The speech spectrum is very sensitive to linear predictive coding (LPC) parameters, so small quantization errors may cause unstable synthesis filter. Line spectral pairs (LSPs) are more efficient representations than LPC parameters. On the other hand, artificial neural networks (ANNs) have been used successfully to improving the quality and also reduction the computational complexity of […]
Variations of speech parameters due to emotion or stress are noticeable. In the presence of such variations, if a neutral model is used for the system, the speech recognition accuracy deteriorates. The evaluation of how emotion influences speech parameters is the first step towards emotional speech recognition. Pitch frequency is an important parameter in speech […]
Emotion has an important role in naturalness of man-machine communication. So, computerized emotion recognition from speech is investigated by many researchers in the recent decades. In this paper, the effect of formant-related features on improving the performance of emotion detection systems is experimented. To do this, various forms and combinations of the first three formants […]
Knowledge embedded within artificial neural networks (ANNs) is distributed over the connections and weights of neurons. So, the user considers ANN as a black box system. There are many researches investigating the area of rule extraction by ANNs. In this paper, a dynamic cell structure (DCS) neural network and a modified version of LERX algorithm […]
The number of attacks in computer networks has grown extensively, and many new intrusive methods have appeared. Intrusion detection is known as an effective method to secure the information and communication systems. In this paper, the performance of Elman and partial-connected dynamic neural network (PCDNN) architectures are investigated for misuse detection in computer networks. To […]
Active queue control aims to improve the overall communication network throughput, while providing lower delay and small packet loss rate. The basic idea is to actively trigger packet dropping (or marking provided by explicit congestion notification (ECN)) before buffer overflow. In this paper, two artificial neural networks (ANN)-based control schemes are proposed for adaptive queue […]
