scholarly journals Zeros of the Zak Transform of averaged totally positive functions

2017 ◽  
Vol 222 ◽  
pp. 55-63
Author(s):  
O.L. Vinogradov ◽  
A.Yu. Ulitskaya
2007 ◽  
Vol 200 (1) ◽  
pp. 255-265 ◽  
Author(s):  
Costanza Conti ◽  
Laura Gori ◽  
Francesca Pitolli

2019 ◽  
Vol 33 (3) ◽  
pp. 723-744 ◽  
Author(s):  
Karlheinz Gröchenig ◽  
Philippe Jaming ◽  
Eugenia Malinnikova

AbstractWe study the question under which conditions the zero set of a (cross-) Wigner distribution W(f, g) or a short-time Fourier transform is empty. This is the case when both f and g are generalized Gaussians, but we will construct less obvious examples consisting of exponential functions and their convolutions. The results require elements from the theory of totally positive functions, Bessel functions, and Hurwitz polynomials. The question of zero-free Wigner distributions is also related to Hudson’s theorem for the positivity of the Wigner distribution and to Hardy’s uncertainty principle. We then construct a class of step functions S so that the Wigner distribution $$W(f,\mathbf {1}_{(0,1)})$$ W ( f , 1 ( 0 , 1 ) ) always possesses a zero $$f\in S \cap L^p$$ f ∈ S ∩ L p when $$p<\infty $$ p < ∞ , but may be zero-free for $$f\in S \cap L^\infty $$ f ∈ S ∩ L ∞ . The examples show that the question of zeros of the Wigner distribution may be quite subtle and relate to several branches of analysis.


Author(s):  
Steven Nahmias ◽  
Frank Proschan

We obtain upper bounds on the number of sign changes of linear combinations of derivatives and convolutions of Polya frequency functions using the variation diminishing properties of totally positive functions. These constitute extensions of earlier results of Karlin and Proschan.


2017 ◽  
Vol 211 (3) ◽  
pp. 1119-1148 ◽  
Author(s):  
Karlheinz Gröchenig ◽  
José Luis Romero ◽  
Joachim Stöckler

1989 ◽  
Vol 3 (3) ◽  
pp. 355-366 ◽  
Author(s):  
Philip J. Boland ◽  
Frank Proschan ◽  
Y. L. Tong

Mixture distributions are a frequently used tool in modelling random phenomena. We consider mixtures of densities from a one-parameter exponenvial family of distributions. Using the tools of totally positive functions and the variation-diminishing property of such, we study the effect of sign-crossing properties of two mixing densities μ1 and μ2 on the resulting mixture distributions f1 and f2. The results enable us to make stochastic and variability cornparisons for binomial-beta, mixed Weibull, and mixed gamma distributions.


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