Signal acquisition, signal reconstruction and analysis of spectrum of the signal are the three most important steps in signal processing and they are found in almost all of the modern day hardware. In most of the signal processing hardware, the signal of interest is sampled at uniform intervals satisfying some conditions like Nyquist rate. However, in some cases the privilege of having uniformly sampled data is lost due to some constraints on the hardware resources. In this thesis an important problem of signal reconstruction and spectral analysis from nonuniformly sampled data is addressed and a variety of methods are presented. The proposed methods are tested via numerical experiments on both artificial and real-life data sets. The thesis starts with a brief review of methods available in the literature for signal reconstruction and spectral analysis from non uniformly sampled data. The methods discussed in the thesis are classified into two broad categories - dense and sparse methods, the classification is based on the kind of spectra for which they are applicable. Under dense spectral methods the main contribution of the thesis is a non-parametric approach named LIMES, which recovers the smooth spectrum from non uniformly sampled data. Apart from recovering the spectrum, LIMES also gives an estimate of the covariance matrix. Under sparse methods the two main contributions are methods named SPICE and LIKES - both of them are user parameter free sparse estimation methods applicable for line spectral estimation. The other important contributions are extensions of SPICE and LIKES to multivariate time series and array processing models, and a solution to the grid selection problem in sparse estimation of spectral-line parameters. The third and final part of the thesis contains applications of the methods discussed in the thesis to the problem of radial velocity data analysis for exoplanet detection. Apart from the exoplanet application, an application based on Sudoku, which is related to sparse parameter estimation, is also discussed.

The detection of low-mass extra-solar planets through radial-velocity searches is currently limited by the intrinsic magnetic activity of the host stars. The correlated noise that arises from their natural radial-velocity variability can easily mimic or conceal the orbital signals of super-Earth and Earth-mass extra-solar planets. I developed an intuitive and robust data analysis framework in which the activity-induced variations are modelled with a Gaussian process that has the frequency structure of the photometric variations of the star, thus allowing me to determine precise and reliable planetary masses. I applied this technique to three recently discovered planetary systems: CoRoT-7, Kepler-78 and Kepler-10. I determined the masses of the transiting super-Earth CoRoT-7b and the small Neptune CoRoT-7c to be 4.73 ± 0.95 M⊕ and 13.56 ± 1.08 M⊕, respectively. The density of CoRoT-7b is 6.61 ± 1.72 g.cm⁻³, which is compatible with a rocky composition. I carried out Bayesian model selection to assess the nature of a previously identified signal at 9 days, and found that it is best interpreted as stellar activity. Despite the high levels of activity of its host star, I determined the mass of the Earth-sized planet Kepler-78b to be 1.76 ± 0.18 M⊕. With a density of 6.2(+1.8:-1.4) g.cm⁻³, it is also a rocky planet. I found the masses of Kepler-10b and Kepler-10c to be 3.31 ± 0.32 M⊕ and 16.25 ± 3.66 M⊕, respectively. Their densities, of 6.4(+1.1:-0.7) g.cm⁻³ and 8.1 ± 1.8 g.cm⁻³, imply that they are both of rocky composition – even the 2 Earth-radius planet Kepler-10c! In parallel, I deepened our understanding of the physical origin of stellar radial-velocity variability through the study of the Sun, which is the only star whose surface can be imaged at high resolution. I found that the full-disc magnetic flux is an excellent proxy for activity-induced radial-velocity variations; this result may become key to breaking the activity barrier in coming years. I also found that in the case of CoRoT-7, the suppression of convective blueshift leads to radial-velocity variations with an rms of 1.82 m.s⁻¹, while the modulation induced by the presence of dark spots on the rotating stellar disc has an rms of 0.46 m.s⁻¹. For the Sun, I found these contributions to be 2.22 m.s⁻¹ and 0.14 m.s⁻¹, respectively. These results suggest that for slowly rotating stars, the suppression of convective blueshift is the dominant contributor to the activity-modulated radial-velocity signal, rather than the rotational Doppler shift of the flux blocked by starspots.