Parameter estimation algorithms utilizing implicit phase. - Michael T. Manry (ICASSP, 1984)

Efficient calculation of signal and noise variances. - Hsien-Chiang Lue; Michael T. Manry (IEEE Trans. Acoust. Speech Signal Process., 1986)

Parameter estimation using the autocorrelation of the discrete Fourier transform. - Michael T. Manry; C. T. Huddleston (ICASSP, 1987)

An efficient, noise tolerant, linear extrapolator. - Phillip J. Thompson; Michael T. Manry (ICASSP, 1988)

Taylor series approximation of the energy spectral density. - Rashid Zia Khan; Lars A. Anderson; Michael T. Manry (IEEE Trans. Acoust. Speech Signal Process., 1988)

A new signal averaging algorithm for discrete signals. - Chun-Chau Lin; Michael T. Manry (IEEE Trans. Acoust. Speech Signal Process., 1989)

Phase improvement in IIR digital filters. - Songqing Shi; Michael T. Manry (IEEE Trans. Acoust. Speech Signal Process., 1989)

Backpropagation representation theorem using power series. - Mu-Song Chen; Michael T. Manry (IJCNN, 1990)

Sigma-pi implementation of a nearest neighbor classifier. - Hung-Chun Yau; Michael T. Manry (IJCNN, 1990)

Sigma-pi implementation of a Gaussian classifier. - Hung-Chau Yau; Michael T. Manry (IJCNN, 1990)

Iterative improvement of a Gaussian classifier. - Hung-Chun Yau; Michael T. Manry (Neural Networks, 1990)

A frequency domain weighting function approach to extrapolation. - Phillip J. Thompson; Michael T. Manry (IEEE Trans. Acoust. Speech Signal Process., 1990)

Iterative improvement of a nearest neighbor classifier. - Hung-Chun Yau; Michael T. Manry (Neural Networks, 1991)

Nonlinear neural network filters for image processing. - Kamyar Rohani; Michael T. Manry (ICASSP, 1992)

Progressive image transmission using a self-supervised back-propagation neural network. - Wei Gong; K. R. Rao 001; Michael T. Manry (J. Electronic Imaging, 1992)

Neural subnet design by direct polynomial mapping. - Kamyar Rohani; Mu-Song Chen; Michael T. Manry (IEEE Trans. Neural Networks, 1992)

Recursive approximation of the energy spectral density. - Lars A. Anderson; Hung-Chun Yau; Michael T. Manry (IEEE Trans. Signal Process., 1992)

Automatic determination of reject thresholds in classifiers employing discriminant functions. - Hung-Chun Yau; Michael T. Manry (IEEE Trans. Signal Process., 1992)

Progressive image transmission. - Wei Gong; K. R. Rao 001; Michael T. Manry (IEEE Trans. Circuits Syst. Video Technol., 1993)

Conventional modeling of the multilayer perceptron using polynomial basis functions. - Mu-Song Chen; Michael T. Manry (IEEE Trans. Neural Networks, 1993)

Classification-based segmentation of ZIP codes. - Yousuf Saifullah; Michael T. Manry (IEEE Trans. Syst. Man Cybern., 1993)

Stochastic Cramer Rao bounds for non-Gaussian signals and parameters. - Weibo Liang; Michael T. Manry; Qiang Yu 001; Michael S. Dawson; Adrian K. Fung (ICASSP, 1995)

Comparisons of a neural network and a nearest-neighbor classifier via the numeric handprint recognition problem. - William E. Weideman; Michael T. Manry; Hung-Chun Yau; Wei Gong (IEEE Trans. Neural Networks, 1995)

Minimum mean square estimation and neural networks. - Michael T. Manry; Steven J. Apollo; Qiang Yu 001 (Neurocomputing, 1996)

A robust statistical-based estimator for soil moisture retrieval from radar measurements. - Michael S. Dawson; Adrian K. Fung; Michael T. Manry (IEEE Trans. Geosci. Remote. Sens., 1997)

Calculation of Cramer Rao maximum a posteriori lower bounds from training data. - Cheng-Hsiung Hsieh; Michael T. Manry; Ting-Cheng Chang (SMC, 1998)

Convergent design of a piecewise linear neural network. - Hema Chandrasekaran; Michael T. Manry (IJCNN, 1999)

Iterative Improvement of trigonometric networks. - Iyab I. Sakhnini; Michael T. Manry; Hema Chandrasekaran (IJCNN, 1999)

A neural network training algorithm utilizing multiple sets of linear equations. - Hung-Han Chen; Michael T. Manry; Hema Chandrasekaran (Neurocomputing, 1999)

Pruning of basis functions in nonlinear approximators. - Hema Chandrasekaran; Hung-Han Chen; Michael T. Manry (Neurocomputing, 2000)

LMS learning algorithms: misconceptions and new results on converence. - Zi-Qin Wang; Michael T. Manry; Jeffrey L. Schiano (IEEE Trans. Neural Networks Learn. Syst., 2000)

New learning factor and testing methods for conjugate gradient training algorithm. - Tae Kim; Michael T. Manry; Javier Maldonado (IJCNN, 2003)

Finding optimal neural network basis function subsets using the Schmidt procedure. - Francisco J. Maldonado; Michael T. Manry; Tae-Hoon Kim (IJCNN, 2003)

A Pseudogenetic Algorithm for MLP Design based upon the Schmidt Procedure. - Francisco J. Maldonado; Michael T. Manry (Neural Networks and Computational Intelligence, 2003)

Adaptive channel equalization for satellite communications with multipath based on unsupervised learning algorithm. - Jiang Li 001; Qilian Liang; Michael T. Manry (PIMRC, 2003)

A semiblind demodulator aided by protocols for wireless ATM network. - Jiang Li 001; Qilian Liang; Michael T. Manry; Tae-Hoon Kim (PIMRC, 2003)

Iterative Improvement of Neural Classifiers. - Jiang Li 001; Michael T. Manry; Li-min Liu; Changhua Yu; John Wei (FLAIRS, 2004)

Prototype Based Classifier Design with Pruning. - Jiang Li 001; Michael T. Manry; Changhua Yu (FLAIRS, 2004)

Invariance of MLP Training to Input Feature De-correlation. - Changhua Yu; Michael T. Manry; Jiang Li 001 (FLAIRS, 2004)

Hidden Layer Training via Hessian Matrix Information. - Changhua Yu; Michael T. Manry; Jiang Li 001 (FLAIRS, 2004)

A nonlinear filtering approach for demodulation over Rician flat fading channels. - Jiang Li 001; Qilian Liang; Michael T. Manry (GLOBECOM, 2004)

Demodulation for wireless ATM network using modified SOM network. - Jiang Li 001; Qilian Liang; Michael T. Manry (ICASSP (5), 2004)

Co-channel interference suppression with model simplification in TDMA systems. - Jiang Li 001; Qilian Liang; Michael T. Manry (PIMRC, 2004)

Nonlinear Network Time-Series Forecasting Using Redundancy Reduction. - Pramod Lakshmi Narasimha; Michael T. Manry; Changhua Yu (FLAIRS, 2005)

Sensitivity of Nonlinear Network Training to Affine Transformed Inputs. - Changhua Yu; Michael T. Manry; Pramod Lakshmi Narasimha (FLAIRS, 2005)

Iterative Design of Neural Network Classifiers Through Regression. - R. G. Gore; Jiang Li 001; Michael T. Manry; Li-min Liu; Changhua Yu; John Wei (Int. J. Artif. Intell. Tools, 2005)

Prototype Classifier Design with Pruning. - Jiang Li 001; Michael T. Manry; Changhua Yu; D. Randall Wilson (Int. J. Artif. Intell. Tools, 2005)

Effects Of Nonsingular Preprocessing On Feedforward Network Training. - Changhua Yu; Michael T. Manry; Jiang Li 001 (Int. J. Pattern Recognit. Artif. Intell., 2005)

A new method to detect obstructive sleep apnea using fuzzy classification of time-frequency plots of the heart rate variability. - Mohammad A. Al-Abed; Khosrow Behbehani; John R. Burk; Edgar A. Lucas; Michael T. Manry (EMBC (Supplement), 2006)

Fast Generation of a Sequence of Trained and Validated Feed-Forward Networks. - Pramod Lakshmi Narasimha; Walter H. Delashmit; Michael T. Manry; Jiang Li 001; Francisco J. Maldonado (FLAIRS, 2006)

An Efficient Feature Selection Algorithm for Computer-aided Polyp Detection. - Jiang Li 001; Jianhua Yao 001; Ronald M. Summers; Nicholas Petrick; Michael T. Manry; Amy K. Hara (Int. J. Artif. Intell. Tools, 2006)

An efficient hidden layer training method for the multilayer perceptron. - Changhua Yu; Michael T. Manry; Jiang Li 001; Pramod Lakshmi Narasimha (Neurocomputing, 2006)

Feature Selection Using a Piecewise Linear Network. - Jiang Li 001; Michael T. Manry; Pramod Lakshmi Narasimha; Changhua Yu (IEEE Trans. Neural Networks, 2006)

A Piecewise Linear Network Classifier. - A. A. Abdurrab; Michael T. Manry; Jiang Li 001; Sanjeev S. Malalur; R. G. Gore (IJCNN, 2007)

A Functional Link Network With Ordered Basis Functions. - Saurabh Sureka; Michael T. Manry (IJCNN, 2007)

Convergent design of piecewise linear neural networks. - Hema Chandrasekaran; Jiang Li 001; Walter H. Delashmit; Pramod Lakshmi Narasimha; Changhua Yu; Michael T. Manry (Neurocomputing, 2007)

Small Models of Large Machines. - Pramod Lakshmi Narasimha; Sanjeev S. Malalur; Michael T. Manry (FLAIRS, 2008)

An integrated growing-pruning method for feedforward network training. - Pramod Lakshmi Narasimha; Walter H. Delashmit; Michael T. Manry; Jiang Li 001; Francisco J. Maldonado (Neurocomputing, 2008)

Upper bound on pattern storage in feedforward networks. - Pramod Lakshmi Narasimha; Michael T. Manry; Francisco J. Maldonado (Neurocomputing, 2008)

Feed-forward network training using optimal input gains. - Sanjeev S. Malalur; Michael T. Manry (IJCNN, 2009)

Training multilayer perceptron by using optimal input normalization. - Xun Cai; Kanishka Tyagi; Michael T. Manry (FUZZ-IEEE, 2011)

Fuzzy C-means clustering based construction and training for second order RBF network. - Kanishka Tyagi; Xun Cai; Michael T. Manry (FUZZ-IEEE, 2011)

Optimal output gain algorithm for feed-forward network training. - Babu Hemanth Kumar Aswathappa; Michael T. Manry; Rohit Rawat (IJCNN, 2011)

An optimal construction and training of second order RBF network for approximation and illumination invariant image segmentation. - Xun Cai; Kanishka Tyagi; Michael T. Manry (IJCNN, 2011)

Analysis and improvement of multiple optimal learning factors for feed-forward networks. - Praveen Jesudhas; Michael T. Manry; Rohit Rawat; Sanjeev S. Malalur (IJCNN, 2011)

Two-Stage Second Order Training in Feedforward Neural Networks. - Melvin Deloyd Robinson; Michael Thomas Manry (FLAIRS, 2013)

Neural decision directed segmentation of silicon defects. - Aditi S. Godbole; Kanishka Tyagi; Michael T. Manry (IJCNN, 2013)

Minimizing validation error with respect to network size and number of training epochs. - Rohit Rawat; Jignesh K. Patel; Michael T. Manry (IJCNN, 2013)

Partially affine invariant training using dense transform matrices. - Melvin Deloyd Robinson; Michael T. Manry (IJCNN, 2013)

Multi-variable Neural Network Forecasting Using Two Stage Feature Selection. - Rohit Rawat; Kunal Vora; Michael T. Manry; Gautam Eapi (ICMLA, 2014)

Optimal Conjugate Gradient Algorithm for Generalization of Linear Discriminant Analysis Based on L1 Norm. - Kanishka Tyagi; Nojun Kwak; Michael T. Manry (ICPRAM, 2014)

An efficient conjugate gradient based learning algorithm for multiple optimal learning factors of multilayer perceptron neural network. - Xun Cai; Kanishka Tyagi; Michael T. Manry; Zhi Chen (IJCNN, 2014)

Multiple optimal learning factors for the multi-layer perceptron. - Sanjeev S. Malalur; Michael T. Manry; Praveen Jesudhas (Neurocomputing, 2015)

Discriminant vector tranformations in neural network classifiers. - Soumitro Swapan Auddy; Kanishka Tyagi; Son Nguyen; Michael T. Manry (IJCNN, 2016)

Second order design of multiclass kernel machines. - Yilong Hao; Kanishka Tyagi; Rohit Rawat; Michael T. Manry (IJCNN, 2016)

Partially affine invariant back propagation. - Son Nguyen; Kanishka Tyagi; Parastoo Kheirkhah; Michael T. Manry (IJCNN, 2016)

Structural adaptation for sparsely connected MLP using Newton's method. - Parastoo Kheirkhah; Kanishka Tyagi; Son Nguyen; Michael T. Manry (IJCNN, 2017)

Second Order Training of a Smoothed Piecewise Linear Network. - Rohit Rawat; Michael T. Manry (Neural Process. Lett., 2017)

Properties of a Batch Training Algorithm for Feedforward Networks. - Melvin Deloyd Robinson; Michael T. Manry; Sanjeev S. Malalur; Changhua Yu (Neural Process. Lett., 2017)

Multi-step Training of a Generalized Linear Classifier. - Kanishka Tyagi; Michael T. Manry (Neural Process. Lett., 2019)

Efficient Machine Learning Approach for Optimizing the Timing Resolution of a High Purity Germanium Detector. - Randall W. Gladen; Varghese A. Chirayath; Alexander J. Fairchild; Michael T. Manry; Ali R. Koymen; Alex H. Weiss (CoRR, 2020)

Second Order Training and Sizing for the Multilayer Perceptron. - Kanishka Tyagi; Son Nguyen; Rohit Rawat; Michael T. Manry (Neural Process. Lett., 2020)

Balanced Gradient Training of Feed Forward Networks. - Son Nguyen; Michael T. Manry (Neural Process. Lett., 2021)

Multistage Newton's Approach for Training Radial Basis Function Neural Networks. - Kanishka Tyagi; Chinmay Rane; Bito Irie; Michael T. Manry (SN Comput. Sci., 2021)

Optimal Input Gain: All You Need to Supercharge a Feed-Forward Neural Network. - Chinmay Rane; Kanishka Tyagi; Sanjeev S. Malalur; Yash Shinge; Michael T. Manry (CoRR, 2023)

Optimizing Performance of Feedforward and Convolutional Neural Networks through Dynamic Activation Functions. - Chinmay Rane; Kanishka Tyagi; Michael T. Manry (CoRR, 2023)

Multiple Gain Adaptations for Improved Neural Networks Training. - Jeshwanth Challagundla; Kanishka Tyagi; Tushar Chugh; Michael T. Manry (CCWC, 2024)

Making Sigmoid-MSE Great Again: Output Reset Challenges Softmax Cross-Entropy in Neural Network Classification. - Kanishka Tyagi; Chinmay Rane; Ketaki Vaidya; Jeshwanth Challagundla; Soumitro Swapan Auddy; Michael T. Manry (CoRR, 2024)

Optimizing performance of feedforward and convolutional neural networks through dynamic activation functions. - Chinmay Rane; Kanishka Tyagi; Adrienne Kline; Tushar Chugh; Michael T. Manry (Evol. Intell., 2024)