12 accepted papers
In this paper, we propose a sparsity and smoothness regularized model for the estimation of nonnegative power spectral densities (PSDs) of complex-valued random processes from mixtures of realizations. The proposed model is designed to jointly estimate frequency components of the realizations and th…
In this paper, we present a novel convex method for the graph-structured sparse recovery. While various structured sparsities can be represented as the graph-structured sparsity, graph- structured sparse recovery remains to be a challenging non-convex problem. To solve this difficulty, we propose a…
We propose a novel convex penalty for block-sparse signals whose block partitions are unknown a priori. We first introduce a nonconvex penalty function, where the block partition is adjusted for the signal of interest by minimizing the mixed ℓ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmln…
In this paper, we propose an over-determined sound source separation method considering the sparsity of impulse responses. Conventional methods, including independent low-rank matrix analysis (ILRMA), have mainly focused on design of realistic sound generation models, but the separation performance…
Speech and audio signal processing frequently requires to recover a time-domain signal from the magnitude of a spectrogram. Conventional methods inversely transform the magnitude spectrogram with a phase spectrogram recovered by the Griffin-Lim algorithm or its accelerated versions. The short-time F…
The nonlinear inverse problem of 2-D phase unwrapping consists in estimating an image, while its pixel values are observed modulo 2π. A variational formulation is considered, which consists in minimizing an energy, convex or not, under the nonconvex data fidelity constraints. We propose a new convex…
Splines are piecewise polynomials and widely used for interpolation and smoothing of observed data, due to their flexibility and optimality in the sense of certain variational problems for one-dimensional (1D) data. However, spline interpolation and smoothing are applicable only to the estimation of…
This paper proposes fast iterative algorithms for solving convexly constrained spline smoothing through a characterization of solutions in a primal-dual space. In view of achievements for fast implementations of spline interpolation, the update of the proposed algorithm is designed as the compositio…
Nguyen and Yamada [NY'13] proposed an adaptive algorithm for fast and stable extraction of the first generalized Hermitian eigenvector and mentioned the extension to the first r generalized eigenvector extraction based on the nested orthogonal complement structure [NTY'12]. However, we recently foun…
Spline is a piecewise polynomial and has been widely used for interpolation and smoothing of observed data. In this paper, with the use of the sufficient condition, derived by Heß and Schmidt, for the nonnegativity of bivariate splines on square grid, we propose two-dimensional positive spline inter…
Two-dimensional (2D) phase unwrapping is a reconstruction problem of a continuous phase, defined over 2D-domain, from its wrapped samples. In our previous work, we presented a two-step phase unwrapping algorithm which first constructs, as the real and imaginary parts of a complex function, a pair of…
Spline is a continuous function piecewise-defined by polynomials and is widely used for interpolation and smoothing of observed data. In 1994, Heβ and Schmidt proposed a positive quartic C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -spline…