Fredric M. Ham

发表

Neural classification of infrasonic signals associated with hazardous volcanic eruptions

Ajay S. Iyer, Fredric M. Ham, Milton Garces, 2011, The 2011 International Joint Conference on Neural Networks.

Synthesis of electromagnetic devices with a novel neural network

Fredric M. Ham, Heriberto Jose Delgado, Michael H. Thursby, 2004, SPIE Defense + Commercial Sensing.

A New Approach for Blind Separation of Convolutive Mixtures

Fredric M. Ham, Ranjan Acharyya, F. Ham, 2007, 2007 International Joint Conference on Neural Networks.

Infrasound signal classification using parallel RBF Neural Networks

R. Acharyya, Kamel Rekab, Fredric M. Ham, 2008 .

Proactive reputation-based defense for MANETs using radial basis function neural networks

Richard Ford, William H. Allen, Eyosias Yoseph Imana, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Neural network architecture for solving the algebraic matrix Riccati equation

Emmanuel G. Collins, Fredric M. Ham, 1996, Defense + Commercial Sensing.

Secure Medial Image Transmission Using Independent Component Analysis of Digitally Modulated Mixtures

Sungjin Park, Fredric M. Ham, 2005, Neural Parallel Sci. Comput..

A MANET simulator (M-SIM) with an extended worm propagation epidemic model

Richard Ford, Fredric M. Ham, Attila Ondi, 2009, 2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers.

Network traffic classification using a parallel neural network classifier architecture

Marco M. Carvalho, Fredric M. Ham, Bereket M. Hambebo, 2011, CSIIRW '11.

Separation of infrasound signals using independent component analysis

Sungjin Park, Fredric M. Ham, Joseph C. Wheeler, 2000, SPIE Defense + Commercial Sensing.

Fourth-Order Cumulants and Neural Network Approach for Robust Blind Channel Equalization

Soowhan Han, Fredric M. Ham, Kwangeui Lee, 2005, ICNC.

Speaker Verification using 3-D ROC Curves for Increasing Imposter Rejections

Young-Chan Lee, Fredric M. Ham, Ranjan Acharyya, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Strategies for Spectrum Allocation in OFDMA Cellular Networks

Marco M. Carvalho, Fredric M. Ham, Bereket M. Hambebo, 2014, LION.

A Neurocomputing Approach for Monitoring Plinian Volcanic Eruptions Using Infrasound

Brian Williams, Fredric M. Ham, Milton Garces, 2012, INNS-WC.

Fuzzy LAPART: a neural architecture for supervised learning through inferencing for stable category recognition

Laurene V. Fausett, Fredric M. Ham, Gabsoo Han, 1995 .

Performance evaluation of static frequency reuse techniques for OFDMA cellular networks

Fredric M. Ham, Bereket M. Hambebo, Bereket Mathewos Hambebo, 2014, Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control.

Reputation Prediction in Mobile Ad Hoc Networks Using RBF Neural Networks

Richard Ford, William H. Allen, Eyosias Yoseph Imana, 2009, EANN.

Low-profile twist reflector design using genetic algorithms

Fredric M. Ham, Brian Lail, Kyu Y. Han, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

A neural network architecture for partial least-squares regression (PLSNET) with supervised adaptive modular Hebbian learning

Ivica Kostanic, Fredric M. Ham, 1998, Neural Parallel Sci. Comput..

Classification of Infrasound Surf Events Using Parallel Neural Network Banks

Young-Chan Lee, Fredric M. Ham, Milton Garces, 2007, 2007 International Joint Conference on Neural Networks.

An infrasonic event neural network classifier

Fredric M. Ham, Joseph C. Wheeler, Thomas A. Leeney, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Extension of the generalized Hebbian algorithm for principal component extraction

Inho Kim, Fredric M. Ham, 1998, Optics & Photonics.

A Universal Neural Networks Based Infrasound Event Classifier

R. Acharyya, Fredric M. Ham, 2006 .

Tracking of moving objects in scenery using subspace projection using independent component analysis

Fredric M. Ham, Brian J. Noe, F. Ham, 2001, SPIE Defense + Commercial Sensing.

Classification of infrasound events using hermite polynomial preprocessing and radial basis function neural networks

Fredric M. Ham, Christopher Lowrie, F. Ham, 2006, SPIE Defense + Commercial Sensing.

A novel neural network for the synthesis of antennas and microwave devices

Fredric M. Ham, Heriberto Jose Delgado, Michael H. Thursby, 2005, IEEE Transactions on Neural Networks.

A robust neural network classifier for infrasound events using multiple array data

Sungjin Park, Fredric M. Ham, Sungjin Park, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

Inverse model formulation of partial least-squares regression: a robust neural network approach

Fredric M. Ham, Thomas M. McDowall, 1998, Defense, Security, and Sensing.

Secure medical-image transmission using independent component analysis

Fredric M. Ham, S. Park, S. Park, 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

Speaker recognition using parallel neural network modules

Fredric M. Ham, Glen Elliott Deal, 2006 .

Discrimination of volcano activity and mountain-associated waves using infrasonic data and a backpropagation neural network

Fredric M. Ham, Joseph C. Wheeler, Thomas A. Leeney, 1999, Defense, Security, and Sensing.

A Universal Neural Network–Based Infrasound Event Classifier

R. Acharyya, Fredric M. Ham, F. Ham, 2006 .

A Scalable Approach to Network Traffic Classification for Computer Network Defense using Parallel Neural Network Classifier Architectures

Marco Carvalho, Fredric M. Ham, Bereket M. Hambebo, 2013 .

Partial least-squares regression neural network (PLSNET) with supervised adaptive modular learning

Ivica Kostanic, Fredric M. Ham, 1996, Defense + Commercial Sensing.

Robust partial least-squares regression: a modular neural network approach

Fredric M. Ham, Thomas M. McDowall, 1997, Defense, Security, and Sensing.

Discrimination of infrasound events using parallel neural network classification banks

Fredric M. Ham, Christopher Lowrie, F. Ham, 2005 .

Robust learning in a partial least-squares neural network

Fredric M. Ham, Thomas M. McDowall, F. Ham, 1997 .