10 accepted papers
We explore applying group theory principles in designing waveforms for a cognitive radar. By leveraging affine groups, we provide a mathematical framework for designing radar waveforms for a wideband multiple-input multiple-output (MIMO) radar. Prior works in this area have considered this approach…
We investigate random projections in the context of randomly projected linear discriminant analysis (LDA). We consider the case in which the data of dimension p is randomly projected onto a lower dimensional space before being fed to the classifier. Using fundamental results from random matrix theor…
Diagnosis of melanoma is fraught with uncertainty, and discordance rates among physicians remain high because of the lack of a definitive criterion. Motivated by this challenge, this paper first introduces the Patch Weyl transform (PWT), a 2-dimensional variant of the Weyl transform. It then present…
In backscatter communications, ultra-low power devices signal by modulating the reflection of radio frequency signals emitted from an external source. Unlike conventional one-way communication, the backscatter channel experiences unique self-interference and spread Doppler clutter. Run-length limite…
We develop a general framework for compressive linear-projection measurements with side information. Side information is an additional signal correlated with the signal of interest. We investigate the impact of side information on classification and signal recovery from low-dimensional measurements.…
High dimensional data is modeled using low-rank subspaces, and the probability of misclassification is expressed in terms of the principal angles between subspaces. The form taken by this expression motivates the design of a new feature extraction method that enlarges inter-class separation, while p…
In this paper, we apply the Weyl transform to represent the vocalization of marine mammals. In contrast to other popular representation methods, such as the MFCC and the Chirplet transform, the Weyl transform captures the global information of signals. This is especially useful when the signal has l…
The Poisson Factor Analysis (PFA) is applied to recover signals from a Poisson compressive sensing system. Motivated by the recently developed compressive X-ray imaging system, Coded Aperture Coherent Scatter Spectral Imaging (CACSSI) [1], we propose a new Bayesian reconstruction algorithm. The prop…
A novel multi-scale dictionary based Bayesian reconstruction algorithm is proposed for compressive X-ray imaging, which encodes the material's spectrum by Poisson measurements. Inspired by recently developed compressive X-ray imaging systems [1], this work aims to recover the material's spectrum fro…
This paper introduces a new ESPRIT-based algorithm to estimate the direction-of-arrival of an arbitrary degree polynomial-phase signal with a single acoustic vector-sensor. The proposed time-invariant ESPRIT algorithm is based on a matrix-pencil pair derived from the time-delayed data-sets collected…