Publications

The accurate estimation of turbulence noise affects many areas of speech processing including separate modification of the noise component, analysis of degree of speech aspiration for treating pathological voice, the automatic labeling of speech voicing, as well as speaker characterization and recognition. Previous work in the literature has provided methods...

When working with network datasets, the theoretical framework of detection theory for Euclidean vector spaces no longer applies. Nevertheless, it is desirable to determine the detectability of small, anomalous graphs embedded into background networks with known statistical properties. Casting the problem of subgraph detection in a signal processing context, this...

Next generation cognitive radios will benefit from the capability of transmitting and receiving communications waveforms across many disjoint frequency channels spanning hundreds of megahertz of bandwidth. The information theoretic advantages of multi-channel operation for cognitive radio (CR), however, come at the expense of stringent linearity requirements on the analog transmit...

The design of an open radar data acquisition system for the Terminal Doppler Weather Radar is presented. Adaptive signal transmission and processing techniques that take advantage of the enhanced capabilities of this new system are also discussed. Results displaying data quality improvements with respect to problems such as range-velocity ambiguity...

As a new radar data acquisition system (RDA) was developed for the Terminal Doppler Weather Radar (TDWR), enhanced signal processing algorithms taking advantage of its increased capabilities were also developed. The primary goals of protecting the base data estimates from range-aliased signals and providing reliable velocity dealiasing were achieved through...

Graphs are canonical examples of high-dimensional non-Euclidean data sets, and are emerging as a common data structure in many fields. While there are many algorithms to analyze such data, a signal processing theory for evaluating these techniques akin to detection and estimation in the classical Euclidean setting remains to be...

This paper considers the problem of obtaining an accurate spectral representation of speech formant structure when the voicing source exhibits a high fundamental frequency. Our work is inspired by auditory perception and physiological studies implicating the use of pitch dynamics in speech by humans. We develop and assess signal processing...

Multi-sensor receivers are commonly tasked with detecting, demodulating and geolocating target emitters over very wide frequency bands. Compressed sensing can be applied to persistently monitor a wide bandwidth, given that the received signal can be represented using a small number of coefficients in some basis. In this paper we present...

Rapid prototyping of advanced signal processing algorithms is critical to developing new radars. Signal processing engineers usually use high level languages like MATLAB, IDL, or Python to develop advanced algorithms and to determine the optimal parameters for these algorithms. Many of these algorithms have very long execution times due to...

Sinewave analysis/synthesis has long been an important tool for audio analysis, modification and synthesis [1]. The recently introduced Fan-Chirp Transform (FChT) [2,3] has been shown to improve the fidelity of sinewave parameter estimates for a harmonic audio signal with rapid frequency modulation [4]. A fast version of the FChT [3]...