Yakov Frayman
Yakov Frayman
Institute of Cybernetics, Behavioral Control and Dynamical Systems, Director
Verified email at alphalink.com.au
TitleCited byYear
A dynamically generated fuzzy neural network and its application to torsional vibration control of tandem cold rolling mill spindles
L Wang, Y Frayman
Engineering Applications of Artificial Intelligence 15 (6), 541-550, 2002
Data mining using dynamically constructed recurrent fuzzy neural networks
Y Frayman, L Wang
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 122-131, 1998
A dynamically-constructed fuzzy neural controller for direct model reference adaptive control of multi-input-multi-output nonlinear processes
Y Frayman, L Wang
Soft Computing 6 (3-4), 244-253, 2002
Solving regression problems using competitive ensemble models
Y Frayman, BF Rolfe, GI Webb
Australian Joint Conference on Artificial Intelligence, 511-522, 2002
Optimal mapping of joint faults into healthy joint velocity space for fault-tolerant redundant manipulators
H Abdi, S Nahavandi, Y Frayman, AA Maciejewski
Robotica 30 (4), 635-648, 2012
Improving an inverse model of sheet metal forming by neural network based regression
Y Frayman, BF Rolfe, GI Webb
ASME 2002 International Design Engineering Technical Conferences and …, 2002
Machine vision system for automatic inspection of surface defects in aluminium die casting
Y Frayman, H Zheng, S Nahavandi
InTech'04: Proceedings of the 5th International Conference on Intelligent …, 2004
A Loop-Shaping Approach to Intelligent Control
Y Frayman, BF Rolfe
Proc. 24th IASTED International Conference on Modelling, Identification and …, 2005
A fuzzy neural network for data mining: dealing with the problem of small disjuncts
Y Frayman, KM Ting, L Wang
IJCNN'99. International Joint Conference on Neural Networks. Proceedings …, 1999
3D depth estimation for visual inspection using wavelet transform modulus maxima
A Bhatti, S Nahavandi, Y Frayman
Computers & Electrical Engineering 33 (1), 48-57, 2007
Recognition of Lubrication Defects in Cold Forging Process with a Neural Network
BF Rolfe, Y Frayman, GL Kelly, S Nahavandi
Artificial Neural Networks in Finance and Manufacturing, 262-275, 2006
Eccentricity and Hardness Control in Cold Rolling Mills with a Dynamically Constructed Neural Controller
Y Frayman, B Rolfe
Intelligence in a Small Materials World, 199, 2005
Adaptive Control of the Closed Loop Behaviour of Manufacturing Processes
T Wilkin, Y Frayman, B Rolfe
ASME 8th Biennial Conference on Engineering Systems Design and Analysis, 313-321, 2006
Cold rolling mill thickness control using the cascade-correlation neural network
Y Frayman, L Wang, C Wan
Control and Cybernetics 31, 327-342, 2002
A fuzzy neural approach to speed control of an elastic two-mass system
Y Frayman, L Wang
Proc. 1997 International Conference on Computational Intelligence and …, 1997
457-199: A Loop-Shaping Approach to Intelligent Control
Y Frayman, BF Rolfe
Direct MRAC with dynamically constructed neural controllers
Y Frayman, L Wang
IJCNN'99. International Joint Conference on Neural Networks. Proceedings …, 1999
Torsionsl Vibration Control of Tandem Cold Rolling Mill Spindles: A Fllzzy Neural Approach
Y Frayman
Proc. IPMM'97, 89-91, 1997
A class of optimal fault tolerant Jacobian for minimal redundant manipulators based on symmetric geometries
H Abdi, S Nahavandi, Y Frayman
2011 IEEE International Conference on Systems, Man, and Cybernetics, 1532-1537, 2011
Predicting the rolling force in hot steel rolling mill using an ensemble model
Y Frayman, B Rolfe, P Hodgson, GI Webb
Artificial intelligence and applications: proceedings of the second IASTED …, 2002
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