Machine learning techniques are commonly used to model complex relationships but implementations on digital hardware are relatively inefficient due to poor matching between conventional computer architectures and the structures of the algorithms they are required to simulate. Neuromorphic devices, and in particular reservoir computing architectures, utilize the inherent properties of physical systems to implement machine learning algorithms and so have the potential to be much more efficient. In this work, we demonstrate that the dynamics of individual domain walls in magnetic nanowires are suitable for implementing the reservoir computing paradigm in hardware.
View Article and Find Full Text PDFFundamental constructs of information theory are applied to quantify the performance of iterated (sequential) Bayesian localization of a time-harmonic source in a range- and time-invariant acoustic waveguide using the segmented Fourier transforms of the received pressure time series. The nonlinear relation, defined by acoustic propagation, between the source location and the received narrowband spectral components is treated as a nonlinear communication channel. The performance analysis includes mismatch between the acoustic channel and the model channel on which the Bayesian inference is based.
View Article and Find Full Text PDFNumerical methods are presented for approximating the probability density functions (pdf's) of acoustic fields and receiver-array responses induced by a given joint pdf of a set of acoustic environmental parameters. An approximation to the characteristic function of the random acoustic field (the inverse Fourier transform of the field pdf) is first obtained either by construction of the empirical characteristic function (ECF) from a random sample of the acoustic parameters, or by application of generalized Gaussian quadrature to approximate the integral defining the characteristic function. The Fourier transform is then applied to obtain an approximation of the pdf by a continuous function of the field variables.
View Article and Find Full Text PDFPlanar magnetic nanowires have been vital to the development of spintronic technology. They provide an unparalleled combination of magnetic reconfigurability, controllability, and scalability, which has helped to realize such applications as racetrack memory and novel logic gates. Microfabricated atom optics benefit from all of these properties, and we present the first demonstration of the amalgamation of spintronic technology with ultracold atoms.
View Article and Find Full Text PDFJ Acoust Soc Am
July 2012
The change-of-variables theorem of probability theory is applied to compute acoustic field and array beam power probability density functions (pdfs) in uncertain ocean environments represented by stratified, attenuating ocean waveguide models. Computational studies for one and two-layer waveguides investigate the functional properties of the acoustic field and array beam power pdfs. For the studies, the acoustic parameter uncertainties are represented by parametric pdfs.
View Article and Find Full Text PDFJ Acoust Soc Am
September 2007
Acoustic communication channel capacity determines the maximum data rate that can be supported by an acoustic channel for a given source power and source/receiver configuration. In this paper, broadband acoustic propagation modeling is applied to estimate the channel capacity for a time-invariant shallow-water waveguide for a single source-receiver pair and for vertical source and receiver arrays. Without bandwidth constraints, estimated single-input, single-output (SISO) capacities approach 10 megabitss at 1 km range, but beyond 2 km range they decay at a rate consistent with previous estimates by Peloquin and Leinhos (unpublished, 1997), which were based on a sonar equation calculation.
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