Dr. Fredric M. Ham Profile

Dr. Fredric M. Ham

SPIE Involvement:

Author

Area of Expertise:

bio-optic sensors

Proceedings Article | 17 April 2006 Paper

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

Christopher Lowrie, Fredric Ham

Proceedings Volume 6247, 624715 (2006) https://doi.org/10.1117/12.661513

KEYWORDS: Neural networks, Signal processing, Neurons, Acoustics, Sensors, Feature extraction, Wavelets, Vector spaces, Signal analyzers, Independent component analysis

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Proceedings Article | 12 April 2004 Paper

Synthesis of electromagnetic devices with a novel neural network

Heriberto Delgado, Michael Thursby, Fredric Ham

Proceedings Volume 5439, (2004) https://doi.org/10.1117/12.549466

KEYWORDS: Electromagnetism, Neural networks, Artificial neural networks, Optimization (mathematics), Antennas, Microwave radiation

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Proceedings Article | 16 August 2001 Paper

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

Brian Noe, Fredric Ham

Proceedings Volume 4380, (2001) https://doi.org/10.1117/12.436978

KEYWORDS: Detection and tracking algorithms, Independent component analysis, Digital filtering, Electronic filtering, Motion models, Spatial filters, Filtering (signal processing), Algorithm development, Image filtering, Statistical analysis

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Proceedings Article | 30 March 2000 Paper

Separation of infrasound signals using independent component analysis

Fredric Ham, Sungjin Park, Joseph Wheeler

Proceedings Volume 4055, (2000) https://doi.org/10.1117/12.380596

KEYWORDS: Independent component analysis, Interference (communication), Principal component analysis, Signal processing, Neural networks, Signal detection, Signal to noise ratio, Sensors, Signal analyzers, Nonlinear optics

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Proceedings Article | 22 March 1999 Paper

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

Fredric Ham, Thomas Leeney, Heather Canady, Joseph Wheeler

Proceedings Volume 3722, (1999) https://doi.org/10.1117/12.342889

KEYWORDS: Neural networks, Sensors, Electroluminescence, Data modeling, Calibration, Binary data, Feature extraction, Speech recognition, Electronic filtering, Neurons

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Proceedings Article | 13 October 1998 Paper

Extension of the generalized Hebbian algorithm for principal component extraction

Fredric Ham, Inho Kim

Proceedings Volume 3455, (1998) https://doi.org/10.1117/12.326722

KEYWORDS: Principal component analysis, Neural networks, Algorithm development, MATLAB, Error analysis, Evolutionary algorithms, Stochastic processes, Neurons, Detection and tracking algorithms, Analog electronics

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Proceedings Article | 25 March 1998 Paper

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

Fredric Ham, Thomas McDowall

Proceedings Volume 3390, (1998) https://doi.org/10.1117/12.304821

KEYWORDS: Data modeling, Calibration, Neural networks, Error analysis, Statistical modeling, Interference (communication), Mathematical modeling, Factor analysis, Matrices, Evolutionary algorithms

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Proceedings Article | 4 April 1997 Paper

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

Thomas McDowall, Fredric Ham

Proceedings Volume 3077, (1997) https://doi.org/10.1117/12.271496

KEYWORDS: Neural networks, Calibration, Statistical modeling, Error analysis, Optimization (mathematics)

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Proceedings Article | 22 March 1996 Paper

Neural network architecture for solving the algebraic matrix Riccati equation

Fredric Ham, Emmanuel Collins

Proceedings Volume 2760, (1996) https://doi.org/10.1117/12.235921

KEYWORDS: Neural networks, Standards development, Adaptive control, Information operations, MATLAB, Chlorine, Electrical engineering, Mechanical engineering, Network architectures, Differential equations

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Proceedings Article | 22 March 1996 Paper

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

Fredric Ham, Ivica Kostanic

Proceedings Volume 2760, (1996) https://doi.org/10.1117/12.235962

KEYWORDS: Calibration, Neural networks, Data modeling, System identification, Factor analysis, Detection and tracking algorithms, Statistical analysis, Absorption, Statistical modeling, Systems modeling

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Showing 5 of 10 publications

SPIE Conference Volume | 5 April 2010

Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII

SPIE Conference Volume | 13 April 2009

Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII

SPIE Conference Volume | 6 May 2008

Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI

Conference Committee Involvement (9)

Independent Component Analyses, Compressive Sampling, Large Data Analyses (LDA), Neural Networks, Biosystems, and Nanoengineering XIII

23 April 2015 | Baltimore, MD, United States

Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII

7 May 2014 | Baltimore, MD, United States

Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI

1 May 2013 | Baltimore, Maryland, United States

Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering X

25 April 2012 | Baltimore, Maryland, United States

Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX

27 April 2011 | Orlando, Florida, United States

Showing 5 of 9 Conference Committees

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