Intonation in unaccompanied singing: Accuracy, drift, and a model of reference pitch memory

Copyright 2014 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The following article appeared in J. Acoust. Soc. Am. 136, 401 (2014) and may be found at http://dx.doi.org/10.1121/1.4881915

Estimating water flow through a hillslope using the massively parallel processor

A new two-dimensional model of water flow in a hillslope has been implemented on the Massively Parallel Processor at the Goddard Space Flight Center. Flow in the soil both in the saturated and unsaturated zones, evaporation and overland flow are all modelled, and the rainfall rates are allowed to vary spatially. Previous models of this type had always been very limited computationally. This model takes less than a minute to model all the components of the hillslope water flow for a day. The model can now be used in sensitivity studies to specify which measurements should be taken and how accurate they should be to describe such flows for environmental studies

Fault diagnosis of operational synchronous digital systems

Diagnosing faults on operational synchronous digital system

Sensitivity analysis Progress report, 1 Mar. - 1 May 1967

Flow graph technique for calculating sensitivity coefficients for electric network

How to cluster in parallel with neural networks

Partitioning a set of N patterns in a d-dimensional metric space into K clusters - in a way that those in a given cluster are more similar to each other than the rest - is a problem of interest in astrophysics, image analysis and other fields. As there are approximately K(N)/K (factorial) possible ways of partitioning the patterns among K clusters, finding the best solution is beyond exhaustive search when N is large. Researchers show that this problem can be formulated as an optimization problem for which very good, but not necessarily optimal solutions can be found by using a neural network. To do this the network must start from many randomly selected initial states. The network is simulated on the MPP (a 128 x 128 SIMD array machine), where researchers use the massive parallelism not only in solving the differential equations that govern the evolution of the network, but also by starting the network from many initial states at once, thus obtaining many solutions in one run. Researchers obtain speedups of two to three orders of magnitude over serial implementations and the promise through Analog VLSI implementations of speedups comensurate with human perceptual abilities

Programming a hillslope water movement model on the MPP

A physically based numerical model was developed of heat and moisture flow within a hillslope on a parallel architecture computer, as a precursor to a model of a complete catchment. Moisture flow within a catchment includes evaporation, overland flow, flow in unsaturated soil, and flow in saturated soil. Because of the empirical evidence that moisture flow in unsaturated soil is mainly in the vertical direction, flow in the unsaturated zone can be modeled as a series of one dimensional columns. This initial version of the hillslope model includes evaporation and a single column of one dimensional unsaturated zone flow. This case has already been solved on an IBM 3081 computer and is now being applied to the massively parallel processor architecture so as to make the extension to the one dimensional case easier and to check the problems and benefits of using a parallel architecture machine

Time varying solar cycle protons program manual

Proton variations in earth radiation belt due to solar cycle - calculation program

Cryptanalysis of a novel cryptosystem based on chaotic oscillators and feedback inversion

An analysis of a recently proposed cryptosystem based on chaotic oscillators and feedback inversion is presented. It is shown how the cryptosystem can be broken when Duffing's oscillator is considered. Some implementation problems of the system are also discussed.Comment: 9 pages, 3 figures, latex forma

Dynamical Phase Transitions In Driven Integrate-And-Fire Neurons

We explore the dynamics of an integrate-and-fire neuron with an oscillatory stimulus. The frustration due to the competition between the neuron's natural firing period and that of the oscillatory rhythm, leads to a rich structure of asymptotic phase locking patterns and ordering dynamics. The phase transitions between these states can be classified as either tangent or discontinuous bifurcations, each with its own characteristic scaling laws. The discontinuous bifurcations exhibit a new kind of phase transition that may be viewed as intermediate between continuous and first order, while tangent bifurcations behave like continuous transitions with a diverging coherence scale.Comment: 4 pages, 5 figure