A new class of large-sample covariance and spectral density matrix estimators is proposed based on the notion of flat-top kernels. The new estimators are shown to be higher-order accurate when ...

Determining an unknown signal from a set of measurements is a fundamental problem in science and engineering. However, as the number of free parameters defining the signal increases, its tomographic ...

Matrix inequalities and means constitute a vibrant area of contemporary mathematical research, blending classical matrix theory with modern applications in numerical analysis, control theory and ...

In this paper, we present new error bounds for the Lanczos method and the shift-and-invert Lanczos method for computing e -τA v for a large sparse symmetric positive ...