We present an efficient spectral projected-gradient algorithm for optimization subject to a group `1-norm constraint. Our approach is based on a novel linear-time algorithm for Euclidean projection onto the `1and group `1-norm constraints. Numerical experiments on large data sets suggest that the proposed method is substantially more efficient and scalable than existing methods.

The efficiency of many speech processing methods rely on accurate modeling of the distribution of the signal spectrum and a majority of prior works suggest that the spectral components follow the Laplace distribution. To improve the probability distribution models based on our knowledge of speech source modeling, we argue that the model should in fact be a multiplicative mixture model, includin...

A class of numerical methods is developed for second order Volterra integrodifferential equations by using a Legendre spectral approach. We provide a rigorous error analysis for the proposed methods, which shows that the numerical errors decay exponentially in the L∞-norm and L-norm. Numerical examples illustrate the convergence and effectiveness of the numerical methods. AMS subject classifica...

We prove that a composition operator is bounded on the Hardy space H of the right half-plane if and only if the inducing map fixes the point at infinity non-tangentially, and has a finite angular derivative λ there. In this case the norm, essential norm, and spectral radius of the operator are all equal to √ λ.

Let X be a d×d symmetric random matrix with independent but non-identically distributed Gaussian entries. It has been conjectured by Lata la that the spectral norm of X is always of the same order as the largest Euclidean norm of its rows. A positive resolution of this conjecture would provide a sharp understanding of the probabilistic mechanisms that control the spectral norm of inhomogeneous ...

In this paper we study the properties of derivations of A B, where A and B are simple separable C*-algebras, and A B is the C*-completion of A B with respect to a C*-norm Yon A B and we will characterize the derivations of A B in terms of the derivations of A and B

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The ε-pseudospectral abscissa αε and radius ρε of an n× n matrix are, respectively, the maximal real part and the maximal modulus of points in its ε-pseudospectrum, defined using the spectral norm. It was proved in [A.S. Lewis and C.H.J. Pang, SIAM J. Optim., 19 (2008), pp. 1048–1072] that for fixed ε > 0, αε and ρε are Lipschitz continuous at a matrix A except when αε and ρε are attained at a ...

We present a new scaleable algorithm for approximating the H∞ norm, an important robust stability measure for linear dynamical systems with input and output. Our spectral value set based method uses a novel hybrid expansion-contraction scheme that, under reasonable assumptions, is guaranteed to converge to a stationary point of the optimization problem defining the H∞ norm, and, in practice, ty...

and Applied Analysis 3 A finite subset of j consecutive positive integers starting with 1 is denoted by j : {1, 2, . . . , j}. The set R−h : −h, 0 ∪ R0 will be used to define the solution of functional differential equations on R0 including its initial condition in −h, 0 . C i R0 ,Rm0 is the set of m-vector real functions of class C i and definition domain R0 and PC i R0 ,Rm0 is the set of m-ve...