Search Results - "Kovvali, N."

Statistics of weak grain boundaries for spall damage in polycrystalline copper by Wayne, L., Krishnan, K., DiGiacomo, S., Kovvali, N., Peralta, P., Luo, S.N., Greenfield, S., Byler, D., Paisley, D., McClellan, K.J., Koskelo, A., Dickerson, R.

“…Correlations between spall damage and local microstructure were investigated using polycrystalline copper samples via laser-driven plate impacts at low…”
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Adaptive learning of behavioral tasks for patients with Parkinson's disease using signals from deep brain stimulation by Zaker, N., Dutta, A., Maurer, A., Zhang, J. J., Hanrahan, S., Hebb, A. O., Kovvali, N., Papandreou-Suppappola, A.

“…We propose adaptive learning methods for identifying different behavioral tasks of patients with Parkinson's disease (PD). The methods use local field…”
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Pseudospectral method based on prolate spheroidal wave functions for frequency-domain electromagnetic simulations by Kovvali, N., Lin, W., Carin, L.

“…We apply prolate spheroidal wave functions of order zero as basis functions in the pseudospectral method for frequency-domain electromagnetic simulation…”
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Ridgelet-based implementation of multiresolution time domain by Lin, W., Kovvali, N., Carin, L.

“…The theory of ridgelet-based analysis of time-domain wave propagation and scattering is developed. Some of the advantages of using ridgelets as compared to…”
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Adaptive learning for damage classification in structural health monitoring by Chakraborty, D, Kovvali, N, Zhang, J J, Papandreou-Suppappola, A, Chattopadhyay, A

“…A key challenge in real-world structural health monitoring (SHM) is diversity of damage phenomena and variability in environmental and operational conditions…”
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A measure of difference between discrete sample sets by Chakraborty, D., Kovvali, N.

“…The estimation of statistical distance between populations is a task of importance for many applications. Conventional methods often rely on the use of a…”
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Direct algorithm for computation of derivatives of the Daubechies basis functions by Lin, Wenbin, Kovvali, Narayan, Carin, Lawrence

“…We extend the direct algorithm for computing the derivatives of the compactly supported Daubechies N-vanishing-moment basis functions. The method yields exact…”
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Electrocardiogram signal modeling using interacting multiple models by Edla, S., Kovvali, N., Papandreou-Suppappola, A.

“…The automatic classification of different heart diseases for monitoring cardiac health through the use of dynamic modeling of electrocardiogram (ECG) signals…”
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EEG/MEG artifact suppression for improved neural activity estimation by Maurer, Alexander, Lifeng Miao, Zhang, Jun Jason, Kovvali, N., Papandreou-Suppappola, A., Chakrabarti, C.

“…Electroencephalography (EEG) and magnetoencephalography (MEG) measurements can be used to monitor neural activity, that is generally characterized using…”
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Beta process based adaptive learning for immunosignature microarray feature identification by Malin, A., Kovvali, N., Papandreou-Suppappola, A., Zhang, J. J., Johnston, S., Stafford, P.

“…We propose a latent feature model for immunosignature random peptide microarray data using beta process factor analysis to identify relationships between…”
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Damage Classification for Structural Health Monitoring Using Time-Frequency Feature Extraction and Continuous Hidden Markov Models by Zhou, W., Chakraborty, D., Kovvali, N., Papandreou-Suppappola, A., Cochran, D., Chattopadhyay, A.

“…We propose an algorithm for the classification of structural damage based on the use of the continuous hidden Markov modeling (HMM) technique. Our approach…”
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Order of accuracy analysis for multiresolution time-domain using Daubechies bases by Kovvali, Narayan, Lin, Wenbin, Carin, Lawrence

“…In this paper, the spatial order of accuracy of multiresolution time‐domain methods using basis functions from the Daubechies family are studied. It is…”
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Image technique for multiresolution time-domain using nonsymmetric basis functions by Kovvali, Narayan, Lin, Wenbin, Carin, Lawrence

“…The image technique is required in order to model perfect‐electric‐conductor and perfect‐magnetic‐conductor boundary conditions using the multiresolution…”
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Adaptive learning of immunosignaturing peptide array features for biothreat detection and classification by Malin, A., Zhang, J. J., Chakraborty, B., Kovvali, N., Papandreou-Suppappola, A., Johnston, S., Stafford, P.

“…As recently discovered, a comprehensive profiling of antibodies in a patient's blood can be obtained using random-sequence peptides on microarrays and analyzed…”
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Adaptive parameter estimation of cardiovascular signals using sequential Bayesian techniques by Edla, S, Zhang, J J, Spanias, J, Kovvali, N, Papandreou-Suppappola, A, Chakrabarti, C

“…Parameter estimation of biological signals such as the electrocardiogram (ECG) is of key clinical significance and can be used to monitor cardiac health and…”
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Analysis of wideband forward looking synthetic aperture radar for sensing land mines by Kovvali, Narayan, Carin, Lawrence

“…Signal processing algorithms are considered for the analysis of wideband, forward looking synthetic aperture radar data and for sensing metal and plastic land…”
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Sequential Markov chain Monte Carlo filter with simultaneous model selection for electrocardiogram signal modeling by Edla, S., Kovvali, N., Papandreou-Suppappola, A.

“…Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance…”
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Real-time closed-loop tracking of an unknown number of neural sources using probability hypothesis density particle filtering by Miao, L., Zhang, J. J., Chakrabarti, C., Papandreou-Suppappola, A., Kovvali, N.

“…Probability hypothesis density (PHD) filtering, implemented using particle filters, is a Bayesian technique used to non-linearly track multiple objects. In…”
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