Novel procedure for characterizing nonlinear systems with memory: 2017 update

Albert H. Nuttall; Richard A. Katz; Derke R. Hughes; Robert M. Koch

doi:10.1117/12.2266413

5 May 2017 Novel procedure for characterizing nonlinear systems with memory: 2017 update

Albert H. Nuttall, Richard A. Katz, Derke R. Hughes, Robert M. Koch

Proceedings Volume 10184, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security, Defense, and Law Enforcement Applications XVI; 101840K (2017) https://doi.org/10.1117/12.2266413
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

The present article discusses novel improvements in nonlinear signal processing made by the prime algorithm developer, Dr. Albert H. Nuttall and co-authors, a consortium of research scientists from the Naval Undersea Warfare Center Division, Newport, RI. The algorithm, called the Nuttall-Wiener-Volterra or 'NWV' algorithm is named for its principal contributors ^{[1], [2],[ 3]} . The NWV algorithm significantly reduces the computational workload for characterizing nonlinear systems with memory. Following this formulation, two measurement waveforms are required in order to characterize a specified nonlinear system under consideration: (1) an excitation input waveform, x(t) (the transmitted signal); and, (2) a response output waveform, z(t) (the received signal). Given these two measurement waveforms for a given propagation channel, a 'kernel' or 'channel response', h= [h₀,h₁,h₂,h₃] between the two measurement points, is computed via a least squares approach that optimizes modeled kernel values by performing a best fit between measured response z(t) and a modeled response y(t). New techniques significantly diminish the exponential growth of the number of computed kernel coefficients at second and third order and alleviate the Curse of Dimensionality (COD) in order to realize practical nonlinear solutions of scientific and engineering interest.

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Albert H. Nuttall, Richard A. Katz, Derke R. Hughes, and Robert M. Koch "Novel procedure for characterizing nonlinear systems with memory: 2017 update", Proc. SPIE 10184, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security, Defense, and Law Enforcement Applications XVI, 101840K (5 May 2017); https://doi.org/10.1117/12.2266413

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KEYWORDS

Complex systems

Algorithm development

Signal processing

Condition numbers

Convolution

Acoustics

Data modeling

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