Dr. Nayda G. Santiago Profile

Dr. Nayda G. Santiago

Assistant Professor at Univ de Puerto Rico Mayagüez

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Publications (7)

SPIE Journal Paper | 6 August 2012 Open Access

Publisher's Note: Evaluation of the graphics processing unit architecture for the implementation of target detection algorithms for hyperspectral imagery

Blas Trigueros-Espinosa, Miguel Velez-Reyes, Nayda Santiago, Samuel Rosario-Torres

JARS, Vol. 6, Issue 01, 060102, (August 2012) https://doi.org/10.1117/12.10.1117/1.JRS.6.060102

KEYWORDS: Graphics processing units, Detection and tracking algorithms, Hyperspectral imaging, Computer architecture, Remote sensing, Image processing, Computer engineering

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SPIE Journal Paper | 21 June 2012 Open Access

Evaluation of the graphics processing unit architecture for the implementation of target detection algorithms for hyperspectral imagery

Blas Trigueros-Espinosa, Miguel Velez-Reyes, Nayda Santiago-Santiago, Samuel Rosario-Torres

JARS, Vol. 6, Issue 01, 061506, (June 2012) https://doi.org/10.1117/12.10.1117/1.JRS.6.061506

KEYWORDS: Detection and tracking algorithms, Sensors, Target detection, Graphics processing units, Hyperspectral imaging, Computer architecture, Statistical analysis, Data processing, Algorithm development, Image processing

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Proceedings Article | 24 May 2012 Paper

Developing a portable GPU library for hyperspectral image processing

Gabriel Pérez-Irizarry, Francisco De La Cruz-Sanchez, Brian Landrón-Rivera, Nayda Santiago, Miguel Velez-Reyes

Proceedings Volume 8390, 839017 (2012) https://doi.org/10.1117/12.920499

KEYWORDS: Hyperspectral imaging, Sensors, Prototyping, Algorithm development, Detection and tracking algorithms, Software development, Image analysis, Linear algebra, Target detection, Software engineering

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Proceedings Article | 20 May 2011 Paper

Evaluation of the GPU architecture for the implementation of target detection algorithms for hyperspectral imagery

Blas Trigueros-Espinosa, Miguel Vélez-Reyes, Nayda Santiago-Santiago, Samuel Rosario-Torres

Proceedings Volume 8048, 80480Q (2011) https://doi.org/10.1117/12.885621

KEYWORDS: Detection and tracking algorithms, Sensors, Target detection, Algorithm development, Hyperspectral imaging, Statistical analysis, Data processing, Computer architecture, Imaging systems, Image processing

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Proceedings Article | 11 April 2008 Paper

Abundance estimation algorithms using NVIDIA CUDA technology

David González, Christian Sánchez, Ricardo Veguilla, Nayda Santiago, Samuel Rosario-Torres, Miguel Vélez-Reyes

Proceedings Volume 6966, 69661E (2008) https://doi.org/10.1117/12.777890

KEYWORDS: Expectation maximization algorithms, Hyperspectral imaging, Field programmable gate arrays, Algorithm development, MATLAB, Graphics processing units, Computer architecture, Computer programming, Visualization, Reconstruction algorithms

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Proceedings Article | 7 May 2007 Paper

An FPGA implementation of image space reconstruction algorithm for hyperspectral imaging analysis

Javier Morales, Nayda Santiago, Alejandro Fernandez

Proceedings Volume 6565, 65651V (2007) https://doi.org/10.1117/12.721282

KEYWORDS: Field programmable gate arrays, Reconstruction algorithms, Hyperspectral imaging, Expectation maximization algorithms, MATLAB, Image analysis, Independent component analysis, Algorithm development, Microcontrollers, Clocks

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Proceedings Article | 17 May 2006 Paper

Performance measures for parameter extraction of sensor array point targets using the discrete chirp Fourier transform

Nayda Santiago, Cesar Aceros Moreno, Domingo Rodriguez

Proceedings Volume 6235, 62351L (2006) https://doi.org/10.1117/12.666465

KEYWORDS: Fourier transforms, Detection and tracking algorithms, Algorithm development, Signal processing, Matrices, Time-frequency analysis, Synthetic aperture radar, Modulation, Sensors, Information fusion

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This work presents a new methodology for the formulation of discrete chirp Fourier transform (DCFT) algorithms and it discusses performance measures pertaining to the mapping of these algorithms to hardware computational structures (HCS) as well as the extraction of chirp rate estimation parameters of multicomponent nonstationary signals arriving from point targets. The methodology centers on the use of Kronecker products algebra, a branch of finite dimensional multilinear algebra, as a language to present a canonical formulation of the DCFT algorithm and its associated properties. The methodology also explains how to search for variants of this canonical formulation that contribute to enhance the mapping process to a target HCS. The parameter extraction technique uses time-frequency properties of the DCFT in a modeled delay-Doppler synthetic aperture radar (SAR) remote sensing and surveillance environment to treat multicomponent return signals of prime length, with additive Gaussian noise as background clutter, and extract associated chirp rate parameters. The fusion of time-frequency information, acquired from transformed chirp or linear frequency modulated (FM) signals using the DCFT, with information obtained when the signals are treated using the discrete ambiguity function acting as point target response, point spread function, or impulse response, is used to further enhance the estimation process. For the case of very long signals, parallel algorithm implementations have been obtained on cluster computers. A theoretical computer performance analysis was conducted on the cluster implementation based on a methodology that applies well-defined design of experiments methods to the identification of relations among different levels in the process of mapping computational operations to high-performance computing systems. The use of statistics for identification of relationships among factors has formalized the search for solutions to the mapping problem and this approach allows unbiased conclusions about results.

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