Parallel Signal Processing Research on the HEP. - Martin T. Hagan; Howard B. Demuth; Paul Hartono Singgih (ICPP, 1985)

Parallel merge-sort algorithms on the HEP. - Paul Hartono Singgih; Howard B. Demuth; Martin T. Hagan; Roger L. Wainwright (ACM Conference on Computer Science, 1986)

Mapping Signal Processing Algorithms on Parallel Architectures. - Nidal M. Sammur; Martin T. Hagan (J. Parallel Distributed Comput., 1990)

Training feedforward networks with the Marquardt algorithm. - Martin T. Hagan; Mohammad B. Menhaj (IEEE Trans. Neural Networks, 1994)

Analysis of Delays in Networked Flight Simulators. - Mohammad B. Menhaj; Martin T. Hagan (IEEE Trans. Syst. Man Cybern. Syst., 1994)

A reduced parameter bilinear time series model. - Yongqing Zhang; Martin T. Hagan (IEEE Trans. Signal Process., 1994)

Levenberg-Marquardt training for modular networks. - Meng-Hock Fun; Martin T. Hagan (ICNN, 1996)

Gauss-Newton approximation to Bayesian learning. - F. Dan Foresee; Martin T. Hagan (ICNN, 1997)

Multireference adaptive noise canceling applied to the EEG. - Christopher J. James; Martin T. Hagan; Richard D. Jones; Philip J. Bones; Grant J. Carroll (IEEE Trans. Biomed. Eng., 1997)

Optimal use of regularization and cross-validation in neural network modeling. - Dingding Chen; Martin T. Hagan (IJCNN, 1999)

Recursive orthogonal least squares learning with automatic weight selection for Gaussian neural networks. - Meng H. Fun; Martin T. Hagan (IJCNN, 1999)

Online least-squares training for the underdetermined case. - Roger L. Schultz; Martin T. Hagan (IJCNN, 1999)

Training multi-loop networks. - Roger L. Schultz; Martin T. Hagan; Orlando De Jesus (IJCNN, 1999)

A new fuzzy logic filter for image enhancement. - Farzam Farbiz; Mohammad Bagher Menhaj; Seyed Ahmad Motamedi; Martin T. Hagan (IEEE Trans. Syst. Man Cybern. Part B, 2000)

Neural Networks: Are Stochastic Global Optimization Methods Worth the Trouble? - Lonnie Hamm; B. Wade Brorsen; Martin T. Hagan (ICMLA, 2002)

Stability of steepest descent with momentum for quadratic functions. - Manabu Torii; Martin T. Hagan (IEEE Trans. Neural Networks, 2002)

Comparison of Stochastic Global Optimization Methods to Estimate Neural Network Weights. - Lonnie Hamm; B. Wade Brorsen; Martin T. Hagan (Neural Process. Lett., 2007)

Backpropagation Algorithms for a Broad Class of Dynamic Networks. - Orlando De Jesus; Martin T. Hagan (IEEE Trans. Neural Networks, 2007)

Backpropagation Through Time for General Dynamic Networks. - Orlando De Jesus; Martin T. Hagan (IC-AI, 2008)

Realizing general MLP networks with minimal FPGA resources. - Carl Latino; Marco A. Moreno-Armendáriz; Martin T. Hagan (IJCNN, 2009)

Spurious Valleys in the Error Surface of Recurrent Networks - Analysis and Avoidance. - Jason Horn; Orlando De Jesus; Martin T. Hagan (IEEE Trans. Neural Networks, 2009)

A procedure for training recurrent networks. - Manh Cong Phan; Mark H. Beale; Martin T. Hagan (IJCNN, 2013)

Error Surface of Recurrent Neural Networks. - Manh Cong Phan; Martin T. Hagan (IEEE Trans. Neural Networks Learn. Syst., 2013)

Relations between local and global perceptual image quality and visual masking. - Md Mushfiqul Alam; Pranita Patil; Martin T. Hagan; Damon M. Chandler (Human Vision and Electronic Imaging, 2015)

A computational model for predicting local distortion visibility via convolutional neural network trainedon natural scenes. - Md Mushfiqul Alam; Pranita Patil; Martin T. Hagan; Damon M. Chandler (ICIP, 2015)

Enhanced recurrent network training. - Amir H. Jafari; Martin T. Hagan (IJCNN, 2015)

Virtual drug screening using neural networks. - Daniel M. Hagan; Martin T. Hagan (IJCNN, 2016)

Advances in Neural Networks and Hybrid-Metaheuristics: Theory, Algorithms, and Novel Engineering Applications. - Marco A. Moreno-Armendáriz; Martin T. Hagan; Enrique Alba 001; José de Jesús Rubio; Carlos Alberto Cruz Villar; Guillermo Leguizamón (Comput. Intell. Neurosci., 2016)

Application of new training methods for neural model reference control. - Amir H. Jafari; Martin T. Hagan (Eng. Appl. Artif. Intell., 2018)

Soft Computing Tools for Virtual Drug Discovery. - Daniel M. Hagan; Martin T. Hagan (J. Artif. Intell. Soft Comput. Res., 2018)

Comparison of neural network NARX and NARMAX models for multi-step prediction using simulated and experimental data. - Joseph Kelley; Martin T. Hagan (Expert Syst. Appl., 2024)