
- Constructive Proof of Efficient Pattern Storage in the Multi-layer Perceptron
- Optimal Pruning of Feedforward Neural Networks Based upon the Schmidt Procedure.
- Convergent Design of A Piecewise Linear Neural Network Hema Chandrasekaran and Michael T. Manry
- Multiple optimal learning factors for feed-forward networks Sanjeev S. Malalur and Michael T. Manry
- 1st Reading February 6, 2005 15:7 WSPC/115-IJPRAI SPI-J068 00402
- Abstract--We report that combining the interbeat heart rate as measured by the RR interval (RR) and R-
- Iterative Improvement of a Nearest Neighbor Classifier Hung-Chun Yau and Michael T. Manry
- MINIMUM MEAN SQUARE ESTIMATION AND NEURAL NETWORKS
- Iterative Improvement of Trigonometric Networks Iyab I. Sakhnini, Michael T. Manry, and Hema Chandrasekaran
- New Training Algorithms for Dependently Initialized Multilayer Perceptrons
- Enhanced Robustness of Multilayer Perceptron Training Walter H. Delashmit
- Fast Generation of a Sequence of Trained and Validated Feed-Forward Pramod L. Narasimha1
- Upper Bound on Pattern Storage in Feedforward Networks Pramod L. Narasimha, Michael T. Manry and Francisco Maldonado
- NEAR-OPTIMAL FLIGHT LOAD SYNTHESIS USING NEURAL NETS
- SHAPE RECOGNITION WITH NEAREST NEIGHBOR ISOMORPHIC NETWORK
- November 28, 2004 22:58 WSPC/INSTRUCTION FILE NNCDesign5 International Journal on Artificial Intelligence Tools
- This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research
- A Modified Hidden Weight Optimization Algorithm for Feed-forward Neural Networks
- Small Models of Large Machines Pramod Lakshmi Narasimha
- + 1kM (1) Abstract--A procedure is presented for selecting and
- This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research
- RESERVOIR INFLOW FORECASTING USING NEURAL NETWORKS CHANDRASHEKAR SUBRAMANIAN
- Proceedings of International Joint Conference on Neural Networks, Atlanta, Georgia, USA, June 14-19, 2009 978-1-4244-3553-1/09/$25.00 2009 IEEE
- Neurocomputing 70 (2007) 10221039 Convergent design of piecewise linear neural networks
- Abstract--A piecewise linear network is discussed which classifies N-dimensional input vectors. The network uses a
- Volume 14(S1) Supplementary August 2007 Dynamics of Continuous,
- Proceedings of the 7th Annual Memphis Area Engineering and Science Conference
- A Neural Network Training Algorithm Utilizing Multiple Sets of Linear Equations
- SIZING OF THE MULTILAYER PERCEPTRON VIA MODULAR NETWORKS
- Evaluation and Improvement of Two Training Algorithms Tae-Hoon Kim, Jiang Li and Michael T. Manry
- Cramer Rao Maximum A-Posteriori Bounds on Neural Network Training Error for Non-Gaussian Signals and Parameters
- IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 17, NO. 5, SEPTEMBER 2006 1101 Feature Selection Using a Piecewise Linear Network