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Journal Articles
- 2024
[j15]Joseph Kelley
, Martin T. Hagan:
Comparison of neural network NARX and NARMAX models for multi-step prediction using simulated and experimental data. Expert Syst. Appl. 237(Part A): 121437 (2024)- 2018
- [j14]Amir H. Jafari, Martin T. Hagan:
Application of new training methods for neural model reference control. Eng. Appl. Artif. Intell. 74: 312-321 (2018) - [j13]Daniel M. Hagan, Martin T. Hagan:
Soft Computing Tools for Virtual Drug Discovery. J. Artif. Intell. Soft Comput. Res. 8(3): 173-189 (2018) - 2016
- [j12]Marco A. Moreno-Armendáriz, Martin T. Hagan, Enrique Alba, José de Jesús Rubio, Carlos Alberto Cruz Villar, Guillermo Leguizamón:
Advances in Neural Networks and Hybrid-Metaheuristics: Theory, Algorithms, and Novel Engineering Applications. Comput. Intell. Neurosci. 2016: 3263612:1 (2016) - 2013
- [j11]Manh Cong Phan, Martin T. Hagan:
Error Surface of Recurrent Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 24(11): 1709-1721 (2013) - 2009
- [j10]Jason Horn, Orlando De Jesus, Martin T. Hagan:
Spurious Valleys in the Error Surface of Recurrent Networks - Analysis and Avoidance. IEEE Trans. Neural Networks 20(4): 686-700 (2009) - 2007
- [j9]Lonnie Hamm, B. Wade Brorsen, Martin T. Hagan:
Comparison of Stochastic Global Optimization Methods to Estimate Neural Network Weights. Neural Process. Lett. 26(3): 145-158 (2007) - [j8]Orlando De Jesus, Martin T. Hagan:
Backpropagation Algorithms for a Broad Class of Dynamic Networks. IEEE Trans. Neural Networks 18(1): 14-27 (2007) - 2002
- [j7]Manabu Torii, Martin T. Hagan:
Stability of steepest descent with momentum for quadratic functions. IEEE Trans. Neural Networks 13(3): 752-756 (2002) - 2000
- [j6]Farzam Farbiz, Mohammad Bagher Menhaj, Seyed Ahmad Motamedi, Martin T. Hagan:
A new fuzzy logic filter for image enhancement. IEEE Trans. Syst. Man Cybern. Part B 30(1): 110-119 (2000) - 1997
- [j5]Christopher J. James, Martin T. Hagan, Richard D. Jones, Philip J. Bones, Grant J. Carroll:
Multireference adaptive noise canceling applied to the EEG. IEEE Trans. Biomed. Eng. 44(8): 775-779 (1997) - 1994
- [j4]Martin T. Hagan, Mohammad B. Menhaj:
Training feedforward networks with the Marquardt algorithm. IEEE Trans. Neural Networks 5(6): 989-993 (1994) - [j3]Mohammad B. Menhaj, Martin T. Hagan:
Analysis of Delays in Networked Flight Simulators. IEEE Trans. Syst. Man Cybern. Syst. 24(6): 875-881 (1994) - [j2]Yongqing Zhang, Martin T. Hagan:
A reduced parameter bilinear time series model. IEEE Trans. Signal Process. 42(7): 1867-1870 (1994) - 1990
- [j1]Nidal M. Sammur, Martin T. Hagan:
Mapping Signal Processing Algorithms on Parallel Architectures. J. Parallel Distributed Comput. 8(2): 180-185 (1990)
Conference and Workshop Papers
- 2016
- [c16]Daniel M. Hagan, Martin T. Hagan:
Virtual drug screening using neural networks. IJCNN 2016: 579-587 - 2015
- [c15]Md Mushfiqul Alam, Pranita Patil, Martin T. Hagan, Damon M. Chandler:
Relations between local and global perceptual image quality and visual masking. Human Vision and Electronic Imaging 2015: 93940M - [c14]Md Mushfiqul Alam, Pranita Patil, Martin T. Hagan, Damon M. Chandler:
A computational model for predicting local distortion visibility via convolutional neural network trainedon natural scenes. ICIP 2015: 3967-3971 - [c13]Amir H. Jafari, Martin T. Hagan:
Enhanced recurrent network training. IJCNN 2015: 1-8 - 2013
- [c12]Manh Cong Phan, Mark H. Beale, Martin T. Hagan:
A procedure for training recurrent networks. IJCNN 2013: 1-8 - 2009
- [c11]Carl Latino, Marco A. Moreno-Armendáriz, Martin T. Hagan:
Realizing general MLP networks with minimal FPGA resources. IJCNN 2009: 1722-1729 - 2008
- [c10]Orlando De Jesus, Martin T. Hagan:
Backpropagation Through Time for General Dynamic Networks. IC-AI 2008: 45-51 - 2002
- [c9]Lonnie Hamm, B. Wade Brorsen, Martin T. Hagan:
Neural Networks: Are Stochastic Global Optimization Methods Worth the Trouble? ICMLA 2002: 9-15 - 1999
- [c8]Dingding Chen, Martin T. Hagan:
Optimal use of regularization and cross-validation in neural network modeling. IJCNN 1999: 1281-1286 - [c7]Meng H. Fun, Martin T. Hagan:
Recursive orthogonal least squares learning with automatic weight selection for Gaussian neural networks. IJCNN 1999: 1496-1500 - [c6]Roger L. Schultz, Martin T. Hagan, Orlando De Jesus:
Training multi-loop networks. IJCNN 1999: 1580-1585 - [c5]Roger L. Schultz, Martin T. Hagan:
Online least-squares training for the underdetermined case. IJCNN 1999: 1870-1875 - 1997
- [c4]F. Dan Foresee, Martin T. Hagan:
Gauss-Newton approximation to Bayesian learning. ICNN 1997: 1930-1935 - 1996
- [c3]Meng-Hock Fun, Martin T. Hagan:
Levenberg-Marquardt training for modular networks. ICNN 1996: 468-473 - 1986
- [c2]Paul Hartono Singgih, Howard B. Demuth, Martin T. Hagan, Roger L. Wainwright:
Parallel merge-sort algorithms on the HEP. ACM Conference on Computer Science 1986: 237-244 - 1985
- [c1]Martin T. Hagan, Howard B. Demuth, Paul Hartono Singgih:
Parallel Signal Processing Research on the HEP. ICPP 1985: 599-606
Coauthor Index
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