09-05-2012, 10:23 AM
Applications of Neural Networks to Telecommunications Systems
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Abstract:
This paper gives an overview of the application of neural networks to telecommunication Systems. Five application areas are discussed, including cloned software identification and the detection of fraudulent use of cellular phones. The systems are summarized and the general results are presented. The conclusions highlight the difficulties involved in using this technology as well as the potential benefits.
In this paper we report on a variety of neural computational systems that have been applied in the telecommunications industry. All the systems described here were developed in collaboration between NORTEL UK and the University of Hertfordshire, UK. In all, five application areas were investigated, resulting in two fully functioning systems, which are incorporated in NORTEL products, two successful prototypes and one application area for which we did not find suitable for a neural computational solution. In the paper we briefly describe the five applications, evaluate our resulting solutions and conclude by reflecting upon the lessons learnt.
What is a system?
System is a set of interacting or interdependent components forming an integrated whole. A system is a set of elements and relationships which are different from relationships of the set or its elements to other elements or sets.
What is a telecommunication system?
In telecommunication, a communications system is a collection of individual communications networks, transmission systems, relay stations, tributary stations, and data terminal equipment (DTE) usually capable of interconnection and interoperation to form an integrated whole. The components of a communications system serve a common purpose, are technically compatible, use common procedures, respond to controls, and operate in unison. Telecommunications is a method of communication.
Telecommunication is the transmission of information over significant distances to communicate. In earlier times, telecommunications involved the use of visual signals, such as beacons, smoke signals, semaphore telegraphs, signal flags, and optical heliographs, or audio messages via coded drumbeats, lung-blown horns, or sent by loud whistles, for example. In the modern age of electricity and electronics, telecommunications now also includes the use of electrical devices such as telegraphs, telephones, and teletypes, the use of radio and microwave communications, as well as fibre optics and their associated electronics, plus the use of the orbiting satellites and the Internet.
A revolution in wireless telecommunications began in the first decade of the 20th century with pioneering developments in wireless radio communications by Nikola Tesla and Guglielmo Marconi, who won the Nobel Prize in Physics in 1909 for his efforts.
Telecommunications play an important role in the world economy and the worldwide telecommunication industry's revenue was estimated to be $3.85 trillion in 2008. The service revenue of the global telecommunications industry was estimated to be $1.7 trillion in 2008, and is expected to touch $2.7 trillion by 2013.
What is an artificial neural network?
An artificial neural network (ANN), usually called neural network (NN), is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes information using a connectionist approach to computation. In most cases an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase. Modern neural networks are non-linear statistical data modelling tools. They are usually used to model complex relationships between inputs and outputs or to find patterns in data.