Research

Thesis and Dissertation Topics

• Approximation theory for discrete transforms (e.g., DFT, DCT, DHT, KLT, &c)

• Approximate computation

• Approximate inference

• Computationally-constrained estimation

• Stochastic analysis of the fast algorithms

• Probability distributions and Entropies

• Non-uniform sampling

• Derivatives and generalizations of the arithmetic Fourier transform

• Not so poor man's Fourier Series

• Non-conventional number representations

• Statistical image processing of SAR data

• Wavelets analysis of biomedical data

• Stockwell transform analysis

• Watermarking based on number theoretic transforms

• Density of Gaussian integer sets and its probabilistic implications

Research Areas

Our group develops original research chiefly in the following areas:

• approximation methods;

• computational statistics;

• low-power, low-complexity circuitry design;

• fast algorithms for DSP and Statistics;

• regression models and likelihood inference;

• efficient numerical computation;

• sampling and interpolation methods

• non-conventional approaches for spectral estimation;

• statistical signal processing;

• image processing for remote sensing;

• signal analysis (analog, discrete, digital; voice, image, video);

• probability distributions and entropies;

• finite field transforms;

• biomedical signal processing.

In statistical jargon, our research is a combination of the following:

• time series analysis (interpolation, sampling, frequency domain methods);

• applied probability;

• statistical computing; and

• applied estimation theory and detection theory.