Abstract
The artificial neural net development has had something of a renaissance in the last decade with an impressive range of application areas. From the viewpoint of telecommunication networks and systems, an increasing number of studies can be observed in recent literature dealing with proposed applications of neural nets in telecommunication environments, such as connection admission control in broadband networks, the control of high-speed interconnection networks, channel allocation in cellular mobile systems, adaptive routing, etc. These proposed applications largely use three main neural net classes: feed-forward nets with backpropagation learning, Hopfield feedback nets, and selforganising neural nets. In this paper, we first give an overview of neural net classes and their main properties, and then present a review of applications in telecommunication systems, where attention is devoted to numerical aspects such as the convergence property and learning speed of the proposed neural nets.
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Alston MD, Chau PM. A decoder for blocked-coded forward error-correcting systems. In: Proceedings IEEE-IJCNN, Washington (DC), 1990; 2: 302–305
Chineh TD, Goodman R. A neural network classifier based on coding theory. In: Proceedings of the 1st Neural Information Processing Systems (NIPS), Denver, CO, 1987: 174–183
Izquierdo AC, Sueiro JC, Mendez AH. Self-organizing feature maps and their application to digital coding of information. In: Proceedings of the International Workshop on Artificial Neural Networks (IWANN'91), Granada, Spain, 1991: 401–408
Jeffries C. Code recognition and set selection with neural networks. Boston: Birkhäuser, 1991
Ortuno I, Delgado JA. Neural networks as error correcting systems in digital communications. In: Proceedings of the International Workshop on Artificial Neural Networks (IWANN'91), Granada, Spain, 1991: 409–414
Vecchi MP, Salehi JA. Neuromorphic networks based on space optical orthogonal codes. In: Proceedings of the 1st Neural Information Processing Systems (NIPS), Denver (CO), 1987: 814–823
Bradburn DS. Reducing transmission error effects using a self-organization network. In: Proceedings IEEE-IJCNN, Washington (DC), 1989; 2: 531–537
Bradburn D. Self-organization of non-numeric data sets. In: Proceedings IEEE-IJCNN, Seattle, WA, 1991; 1: 37–41
Manikopoulos C, Antoniou G, Metzelopoulou S. ANS classification of finite state machine for high compression video conference coding. Poster presentation at the IEEE-INNC, Paris, France, 1990; 1: 55
Matsumoto T, Koga M, Noguchi K, Aizawa S. Proposal for neural-network applications to fibreoptic transmission. In: Proceedings IEEE-IJCNN, San Diego (CA), 1990; 1: 75–80
Gibson GJ, Siu S, Cowan CF. Multi-layer perceptron structures applied to adaptive equalizers for data communications. In: Proceedings of ICASSP, 1989; 1183–1186
Koers PHJ, Vogel JA, Zeelen R, van der Putten FG, Berkhout AJ. Active noise reduction using a neural network processing system. In: Proceedings IEEE-INNC, Paris, France, 1990; 1: 145–148
Kohonen T, Raivio K, Simula O, Ventä O, Henriksson J. An adaptive discrete-signal detector based on self-organizing maps. In: Proceedings IEEE-IJCNN, Washington (DC), 1990; 2: 249–252
Kohonen T, Raivio K, Simula O, Ventä O, Henriksson J. Combining linear equalization and self-organizing adaptation in dynamic discrete-signal detection. In: Proceedings IEEE-IJCNN, San Diego (CA), 1990; 1: 223–228
Matthews MB, Moschytz GS. Neural network nonlinear adaptive filtering using the extended Kalman filter algorithms. In: Proceedings IEEE-INNC, Paris, France, 1990; 1: 115–118
Nobakht RA, Van den Bout DE, Townsend JK, Ardalan SH. Optimization of transmitter and receive filters for digital communication systems using mean field annealing. IEEE J Selected Areas in Commun 1990; 8(8): 1472–1479
Stubbendieck GT, Oldham WJB. Recognition of patterns in electronic communication signals using neural networks. In: Knowledge-based systems and neural networks, eds: Sharda R. et al., Amsterdam: Elsevier, 1991
Hopfield JJ. Neurons with graded response have collective computational properties like those twostate neurons. In: Proceedings of the National Academy of Sciences USA 81, May 1984: 3088–3092
Hopfield JJ, Tank DW. Neural computations of decisions in optimization problems. Biol Cybern 1985; 52: 141–152
Parks PC, Hahn V. Stability theory. (In German). Berlin: Springer-Verlag, 1981
Müller B, Reinhardt J. Neural networks—an introduction. Berlin: Springer-Verlag, 1990
Watrous RL. Learning algorithms for connectionist networks: Applied gradient methods of non-linear optimization. In: Proceedings of IEEE International Conference on Neural Networks, 1987; II: S; 619–627
Kohonen T. Self-organization and associative memory (2nd ed.). Berlin: Springer-Verlag, 1988
Ritter H, Martinetz Th, Schulten K. Neural nets: an introduction to neural computer science of selforganising networks. Reading (MA): Addison-Wesley, 1990
Kohonen T, Kangas J, Laaksonen J, Simula O, Ventä O. Variants of self-organizing maps. In: Proceedings IEEE-IJCNN, Washington (DC), 1989; 2: 517–522
De Sieno, D. Adding a conscience to competitive learning. In: Proceedings IEEE-ICNN, 1988; I: 117–124
Tanenbaum AS. Computer networks. Englewood Cliffs (NJ): Prentice-Hall, 1988
Rauch HE, Winarske T. Neural networks for routing communication traffic. IEEE Control Syst Mag 1988: 26–30
Zhang L, Thomopoulos SCA. Neural network implementation of the shortest path algorithm for traffic routing in communication networks. Private communication
Ali MM, Kamoun F. A neural network shortest path algorithm for optimum routing in packet-switched communications networks. In: Proceedings GLO-BECOM, 1991; 0120–0124
Fritsch T, Mandel W. Communication network routing using neural nets. Research Report, No. 30, Institute of Computer Science, University of Würzburg, 1991
Fritsch T, Mandel W. Communication network routing using neural nets — numerical aspects and alternative approaches. In: Proceedings IEEE-IJCNN, Singapore, 1991; 1: 752–757
Jensen JE, Eshera MA, Barash SC. Neural network controller for adaptive routing in survivable communication networks. In: Proceedings IEEE-IJCNN, San Diego (CA), 1990; 2: 29–36
Frisiani G, Parisini T, Siccardi L, Zoppoli R. Team theory and back-propagation for dynamic routing in communication networks. In: Proceedings IEEE-IJCNN, Seattle (WA), 1991; 1: 325–334
Thomopoulos SCA, Zhang L, DerWann C. Neural network implementation of the shortest path algorithm for traffic routing in communication networks. In: Proceedings IEEE-IJCNN, Singapore, 1991; 3: 2693–2702
Grigorieff RD. Numerics of ordinary differential equations. (In German). Teubner, 1977
Aiyer SVB, Niranjan M, Fallside F. A theoretical investigation into the performance of the Hopfield model. IEEE Trans Neural Networks (1990); 1(2): 204–215
Bertsekas D, Gallager R. Data networks. Englewood Cliffs: Prentice-Hall, 1987
Wieselthier JE, Barnhart CM, Ephremides A. The application of Hopfield Neural Network Techniques to Problems of Routing and Scheduling in Packet Radio Networks. NRL Memorandum Report 6730, Naval Research Laboratory, Washington, 1990
Hajek B, Sasaki G. Link scheduling in polynomial time. IEEE Trans Information Theory 1988; 34: 910–917
Aicardi M, Davoli F, Minciardi R, Toccalino M, Traversa R, Zoppoli R. A neural network approach for adaptive decentralized routing in communication networks. In: Proceedings 29th IEEE Conference on Decision and Control. Hawaii, 1990
COST 224 Committee (ed. Roberts J.), COST 224 Final report: Performance evaluation and design of multiservice networks. Paris, France, October 1991
Hiramatsu A. ATM communications network control by neural networks. In: Proceedings IEEE-IJCNN, Washington (DC), 1989; 1: 259–266
Hiramatsu A. ATM communications network control by neural networks. IEEE Trans Neural Networks 1990; 1: 122–130
Kunz D. Practical channel assignment. In: Proceedings of the IEEE, 1990: 652–655
Duque AM, Kunz D. Parallel algorithms for channel assignment in cellular mobile radio systems: the neural network approach. In: Parallel processing in neural systems and computers, eds: Eckmiller R, Hartmann G, Hauske G, 1990
Chan PTH, Palaniswami M, Everitt D. Dynamical channel assignment for cellular mobile radio system using feedforward neural networks. In: Proceedings IEEE-IJCNN, Singapore, 1991; 2: 1242–1247
Everitt DE, MacFayden NM. Analysis of multicellular mobile radiotelephone systems with loss. Br Telecom Technol J 1983; 1(2)
Ansari N, Chen Y. Dynamic digital satellite communication network management by self-organization. In: Proceedings IEEE-IJCNN, Washington (DC), 1990; 2: 567–570
Morris RJT. Prospects for neural networks in broadband network resource management. In: Proceedings 13th ITC: Teletraffic and Datatraffic in a period of change, Copenhagen, Denmark, June 1991; 335–340
Milito RA, Guyon I, Solla SA. Neural network implementation of admission control. Advances in Neural Information Processing Systems (NIPS), 1991: 4
Tran-Gia P, Gropp O. Structure and performance of neural nets in broadband system admission control. Research Report, No. 37, Institute of Computer Science, University of Würzburg, December 1991
Marrakchi A, Troudet T. A neural net arbitrator for large crossbar packet-switches. IEEE Trans Circuits and Syst 1989; 36(7): 1039–1041
Ali MM, Nguyen HT. A neural network implementation of an input access scheme in a high-speed packet switch. In: Proceedings GLOBECOM, 1989; 1192–1197
Brown TX. Neural networks for switching. IEEE Commun Mag 1989: 72–81
Brown TX, Kuo-Hui L. Neural network design of a banyan network. IEEE J Selected Areas Commun 1990; 8: 1428–1438
Ali MM, Nguyen HT. A neural network controller for a high-speed packet switch. In: Proceedings International Telecommunications Symposium, 1990; 493–497
Jungnickel D. Graphen, Netzwerke und Algorithmen. (In German). Bibliographisches Institut, Mannheim, 1990
Tagliarini RG, Christ JF, Page EW. Optimization using neural networks. IEEE Trans Comput 1991; 40(12): 533–541
Ali MM, Youssefi M. The performance analysis of an input access scheme in a high-speed packet switch. In: Proceedings INFOCOM, 1991; 0454–0461
Mittler M, Tran-Gia P. Performance of a neural net scheduler used in packet switching interconnection networks. In: Proceedings IEEE International Conference on Neural Networks, San Francisco, CA, 1993, 2: 695–700
Ghosh J, Hukkoo A, Varma A. Neural networks for fast arbitration and switching noise reduction in large crossbars. In: Proceedings of the International Neural Network Conference (INNC) of the IEEE, Paris, France 1990; 1: 270–273
Ahmadi H, Denzel WE. A survey of modern highperformance switching techniques. IEEE J Selected Areas in Commun 1989; 7(7): 1091–1103
Sun KT, Fu HC. A neural network algorithm for solving the traffic control problem in multistage interconnection networks. In: Proceedings IEEEIJCNN, Singapore, 1991; 2: 1136–1141
Ansari N, Liu D. The performance evaluation of a new neural network based traffic management scheme for a satellite communication network. In: Proceedings GLOBECOM, 1991; 0110–0114
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Fritsch, T., Mittler, M. & Tran-Gia, P. Artificial neural net applications in telecommunication systems. Neural Comput & Applic 1, 124–146 (1993). https://doi.org/10.1007/BF01414432
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DOI: https://doi.org/10.1007/BF01414432