Electrical and Electronic Engineering - Research Publications
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ItemCurvature-constrained directional-cost paths in the plane(SPRINGER, 2012-08)
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ItemGradient-Constrained Minimum Networks. III. Fixed Topology(SPRINGER/PLENUM PUBLISHERS, 2012-10)
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ItemMaximizing the net present value of a Steiner tree(Springer US, 2015)The theory of Steiner trees has been extensively applied in physical network design problems to locate a Steiner point that minimizes the total length of a tree. However, maximizing the total generated cash flows of a tree has not been investigated. Such a tree has costs associated with its edges and values associated with nodes. In order to reach the nodes in the tree, the edges need to be constructed. The edges are constructed in a particular order and the costs of constructing the edges and the values at the nodes are discounted over time. These discounted costs and values generate cash flows. In this paper, we study the problem of optimally locating a single Steiner point so as to maximize the sum of all the discounted cash flows, known as the net present value (NPV). An application of this problem occurs in underground mining where, we want to optimally locate a junction point in the underground access network to maximize the NPV. We propose an efficient iterative algorithm to optimally locate a single degree-3 Steiner point. We show this algorithm converges quickly and the Steiner point is unique subject to realistic design parameters.
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ItemOn the history of the Euclidean Steiner tree problem(SPRINGER, 2014-05)
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ItemOptimal curvature-constrained paths for general directional-cost functions(SPRINGER, 2013-09)
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ItemDelay Selection by Spike-Timing-Dependent Plasticity in Recurrent Networks of Spiking Neurons Receiving Oscillatory Inputs(PUBLIC LIBRARY SCIENCE, 2013-02)Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem.
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ItemNo Preview AvailableOptimal curvature and gradient-constrained directional cost paths in 3-space(Springer Verlag, 2015-07-01)
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ItemA Comparative Testing Study of Commercial 18650-Format Lithium-Ion Battery Cells(ELECTROCHEMICAL SOC INC, 2015)