Highly Scalable Matching Pursuit Signal Decomposition Algorithm

A Publication, Ashok Srivastava's Collection - 10 years, 3 months ago

Shared By: Ashok Srivastava

In this research, we propose a variant of the classical Matching Pursuit Decomposition (MPD) algorithm with significantly improved scalability and computational performance. MPD is a ...

Data Mining at NASA: From Theory to Applications

A Publication, Ashok Srivastava's Collection - 10 years, 3 months ago

Shared By: Ashok Srivastava

NASA has some of the largest and most complex data sources in the world, with data sources ranging from the earth sciences, space sciences, and ...

Classification of Damage Signatures in Composite Plates using On

A Publication, Santanu Das's Collection - 13 years, 7 months ago

Shared By: Santanu Das

Damage characterization through wave propagation and scattering is of considerable interest to many non-destructive evaluation techniques. For fiber-reinforced composites, complex waves can be generated during ...

Predicting Engine Parameters using the Optical Spectrum

A Publication, Ashok Srivastava's Collection - 10 years, 3 months ago

Shared By: Ashok Srivastava

The Optical Plume Anomaly Detection (OPAD) system is under development to predict engine anomalies and engine parameters of the Space Shuttle's Main Engine (SSME). The ...

Discovery of Recurring Anomalies in Text Reports

A Publication, Ashok Srivastava's Collection - 10 years, 3 months ago

Shared By: Ashok Srivastava

This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining algorithms to ...

Onboard Detection of Snow, Ice, Clouds, and Other Processes

A Publication, Ashok Srivastava's Collection - 10 years, 3 months ago

Shared By: Ashok Srivastava

The detection of clouds within a satellite image is essential for retrieving surface geophysical parameters from optical and thermal imagery. Even a small percentage of ...

Mixture Density Mercer Kernels: A Method to Learn Kernels

A Publication, Ashok Srivastava's Collection - 10 years, 3 months ago

Shared By: Ashok Srivastava

This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian ...

Characterizing Variability and Multi-Resolution Predictions

A Publication, Ashok Srivastava's Collection - 10 years, 3 months ago

Shared By: Ashok Srivastava

In previous papers, we introduced the idea of a Virtual Sensor, which is a mathematical model trained to learn the potentially nonlinear relationships between spectra ...

Ensemble Approach to Building Mercer Kernels

A Publication, Ashok Srivastava's Collection - 10 years, 3 months ago

Shared By: Ashok Srivastava

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive ...