We introduce a new method of Bayesian wavelet shrinkage for reconstructing a signal when we observe a noisy version. Rather than making the usual assumption that the wavelet coefficients of the signal are independent, we allow for the possibility that they are locally correlated in both location (time) and scale (frequency). This leads us to a prior structure which is, unfortunately, analytical...

to review the diffrent aspects of gender, subtype of cah, management and results in all our patients with ambiguous genitalia diagnosed as congenital adrenal hyperplasia during the past 30 years. methods: the files of all our patients with cah reviewed retrospectively. results: out of 256 patients who had ambiguous genitalia due to cah, 96% were female and 4% were male. 21-ohd was diagnosed in ...

We investigate the memorability of data represented in two different visualization designs. In contrast to recent studies that examine which types of visual information make visualizations memorable, we examine the effect of different visualizations on time and accuracy of recall of the displayed data, minutes and days after interaction with the visualizations. In particular, we describe the re...

Inspired by the Penrose-Hameroff thesis, we are intuitively led to examine an intriguing correspondence of ‘induction’ (by fields), with the complex phenomenon of (metabolism-sustained) consciousness: Did sequences of associated induction patterns in field-susceptible biomatter have simpler beginnings?

We introduce a new method of Bayesian wavelet shrinkage for reconstructing a signal when we observe a noisy version. Rather than making the usual assumption that the wavelet coefficients of the signal are independent, we assume that they are locally correlated in both location (time) and scale (frequency). This leads us to prefer a novel prior structure to which is, unfortunately, analytically ...

[*] Dr. S. Kowarik,[þ] Dr. A. Gerlach, Dr. S. Sellner Prof. F. Schreiber Institut f€ ur Angewandte Physik, Universit€ at T€ ubingen 72076 T€ ubingen, Germany E-mail: [email protected] Dr. L. Cavalcanti ESRF, 6 Rue Jules Horowitz Boı̂te Postale 220, 38043 Grenoble Cedex 9, France [þ] Present address: Department of Chemistry, University of California, Berkeley CA 94720, USA [**] Acknowle...

The paper is concerned with the Bayesian analysis of point processes which are observed with noise. It is shown how to produce exact samples from the posterior distribution of the unobserved true point pattern given a noisy observation. The algorithm is a perfect simulation method which applies dominated Coupling From The Past (CFTP) to a spatial birth-and-death process. Dominated CFTP is made ...