Application of decision feedback equalisers based on multilayer neural network structures to compensate for optical fibre dispersion and nonlinearity

IET Optoelectronics ◽

10.1049/iet-opt:20060097 ◽

2007 ◽

Vol 1 (4) ◽

pp. 169-174

Author(s):

L. Yunxi

Keyword(s):

Neural Network ◽

Optical Fibre ◽

Decision Feedback ◽

Network Structures

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Decision feedback equalisation using neural network structures and performance comparison with standard architecture

IEE Proceedings I Communications Speech and Vision ◽

10.1049/ip-i-2.1990.0031 ◽

1990 ◽

Vol 137 (4) ◽

pp. 221 ◽

Author(s):

G.J. Gibson ◽

S. Siu ◽

C.F.N Cowan

Keyword(s):

Neural Network ◽

Performance Comparison ◽

Decision Feedback ◽

Network Structures ◽

And Performance

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Hierarchical Neural Network Structures for Phoneme Recognition

10.1007/978-3-642-34425-1 ◽

2013 ◽

Author(s):

Daniel Vasquez ◽

Rainer Gruhn ◽

Wolfgang Minker

Keyword(s):

Neural Network ◽

Network Structures ◽

Phoneme Recognition ◽

Hierarchical Neural Network

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Extending the response range of an optical fibre pH sensor using an artificial neural network

Analytica Chimica Acta ◽

10.1016/0003-2670(96)00149-3 ◽

1996 ◽

Vol 330 (1) ◽

pp. 31-40 ◽

Author(s):

Mohd N. Taib ◽

Roberto Andres ◽

Ramaier Narayanaswamy

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Optical Fibre ◽

Ph Sensor ◽

Response Range ◽

Artificial Neural

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Adaptive decision feedback equalizer for SISO communication channel using combined FIR-neural network and fast block LMS algorithm

2016 IEEE Annual India Conference (INDICON) ◽

10.1109/indicon.2016.7839048 ◽

2016 ◽

Author(s):

Harish K. Sahoo ◽

Basabdatta Mohanty

Keyword(s):

Neural Network ◽

Communication Channel ◽

Decision Feedback ◽

Lms Algorithm ◽

Decision Feedback Equalizer

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Optimisation of the range of an optical fibre pH sensor using feed-forward artificial neural network

Sensors and Actuators B Chemical ◽

10.1016/s0925-4005(03)00025-x ◽

2003 ◽

Vol 90 (1-3) ◽

pp. 175-181 ◽

Author(s):

Faiz Bukhari Mohd Suah ◽

Musa Ahmad ◽

Mohd Nasir Taib

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Optical Fibre ◽

Ph Sensor ◽

Feed Forward ◽

Artificial Neural

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A Unified Approach to Derive Gradient Algorithms for Arbitrary Neural Network Structures

ICANN ’94 ◽

10.1007/978-1-4471-2097-1_127 ◽

1994 ◽

pp. 545-548

Author(s):

Françoise Beaufays ◽

Eric A. Wan

Keyword(s):

Neural Network ◽

Network Structures ◽

Unified Approach ◽

Gradient Algorithms

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Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures

Lecture Notes in Computer Science - Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning ◽

10.1007/978-3-030-30484-3_33 ◽

2019 ◽

pp. 393-405 ◽

Author(s):

Shota Saito ◽

Shinichi Shirakawa

Keyword(s):

Neural Network ◽

Dynamic Optimization ◽

Probabilistic Model ◽

Model Complexity ◽

Network Structures ◽

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Optical high order feedback neural network using an optical fibre amplifier

Artificial Neural Networks ◽

10.1016/b978-0-444-89488-5.50140-8 ◽

1992 ◽

pp. 1479-1482

Author(s):

Z.Q. Mao ◽

D.R. Selviah ◽

J.E. Midwinter

Keyword(s):

Neural Network ◽

Optical Fibre ◽

Fibre Amplifier ◽

Feedback Neural Network

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A new indirect encoding method with variable length gene code to optimize neural network structures

IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339) ◽

10.1109/ijcnn.1999.830879 ◽

2003 ◽

Author(s):

K. Kobayashi ◽

M. Ohbayashi

Keyword(s):

Neural Network ◽

Variable Length ◽

Network Structures ◽

Gene Code ◽

Indirect Encoding ◽

Encoding Method

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A dual element multipoint optical fibre water contamination sensor system utilising artiflcial neural network pattern recognition.

Proceedings of IEEE Sensors 2003 (IEEE Cat. No.03CH37498) ◽

10.1109/icsens.2003.1278966 ◽

2004 ◽

Author(s):

D. King ◽

W.B. Lyons ◽

C. Flanagan ◽

E. Lewis

Keyword(s):

Neural Network ◽

Pattern Recognition ◽

Optical Fibre ◽

Water Contamination ◽

Sensor System ◽

Network Pattern

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