相关论文: Impact of Spectral Coverage on Parameter recovery …

The spectrogram is a classical DSP tool used to view signals in both time and frequency. Unfortunately, the Heisenberg Uncertainty Principal limits our ability to use them for detecting and measuring narrowband signal modulation in wideband…

Statistical inference on graphs often proceeds via spectral methods involving low-dimensional embeddings of matrix-valued graph representations, such as the graph Laplacian or adjacency matrix. In this paper, we analyze the asymptotic…

We present a new approach to constrain the spectral energy distribution of the intergalactic UV background observationally by studying metal absorption systems. We study single-component metal line systems exhibiting various well-measured…

We present the results of the power spectral density (PSD) analysis for the blazars Mrk\,421 and PKS\,2155$-$304, using good-quality, densely sampled light curves at multiple frequencies, covering 17 decades of the electromagnetic spectrum,…

Recent works have developed samples of blazars from among the Fermi-LAT unassociated sources via machine learning comparisons with known blazar samples. Continued analysis of these new blazars tests the predictions of the blazar sequence…

Rapid inverse Compton cooling sets in when the brightness temperature (T_B) of a self-absorbed synchrotron source with power-law electrons reaches ~10^{12} K. However, T_B inferred from observations of intra-day variable sources (IDV) are…

We discuss a technique for mapping the synchrotron turnover frequency distribution using nearly simultaneous, multi--frequency VLBI observations. The limitations of the technique arising from limited spatial sampling and frequency coverage…

In this paper, we present strip-map mode spaceborne Synthetic Aperture Radar (SAR) imaging with the focus on Doppler centroid frequency estimation. The non-zero Doppler centroid frequency is the result of non-zero squint angle which if it…

Speckle based imaging consists of forming a super-resolved reconstruction of an unknown sample from low-resolution images obtained under random inhomogeneous illuminations (speckles). In a blind context where the illuminations are unknown,…

Natural images tend to mostly consist of smooth regions with individual pixels having highly correlated spectra. This information can be exploited to recover hyperspectral images of natural scenes from their incomplete and noisy…

A representation in the form of spectral parameter power series (SPPS) is given for a general solution of a one dimension Dirac system containing arbitrary matrix coefficient at the spectral parameter, \[ B \frac{dY}{dx} + P(x)Y = \lambda…

We study the problem of exact support recovery for high-dimensional sparse linear regression under independent Gaussian design when the signals are weak, rare, and possibly heterogeneous. Under a suitable scaling of the sample size and…

Spectro-microscopy is an experimental technique which can be used to observe spatial variations in chemical state and changes in chemical state over time or under experimental conditions. As a result it has broad applications across areas…

Using tools from stochastic geometry, we develop a framework to model the downlink rate coverage probability of a user in a given small cell network (SCN) with massive MIMO-enabled wireless backhauls. The considered SCN is composed of a…

Estimation of the angular power spectrum of the Cosmic Microwave Background (CMB) on a small patch of sky is usually plagued by serious spectral leakage, specially when the map has a hard edge. Even on a full sky map, point source masks can…

We consider the problem of exact community recovery in the Labeled Stochastic Block Model (LSBM) with $k$ communities, where each pair of vertices is associated with a label from the set $\{0,1, \dots, L\}$. A pair of vertices from…

We present results of an extensive suite of numerical simulations that probe square-tiled microwave absorber performance as a function of material properties, frequency, geometry, and unit cell size. The work, which probes both specular…

Estimation of the covariance structure of spatial processes is of fundamental importance in spatial statistics. In the literature, several non-parametric and semi-parametric methods have been developed to estimate the covariance structure…

Enlightening our understanding of the first galaxies responsible for driving reionisation requires detecting the 21-cm signal from neutral hydrogen. Interpreting the wealth of information embedded in this signal requires Bayesian inference.…

This thesis proposes spatio-spectral techniques for hyperspectral image analysis. Adaptive spatio-spectral support and variable exposure hyperspectral imaging is demonstrated to improve spectral reflectance recovery from hyperspectral…