In [1], Duprat and Muller introduced the ingenious “Branching CORDIC” algorithm. It enables a fast implementation of CORDIC algorithm using signed digits and requires a constant normalization factor. This correspondence corrects some errors in the original paper. All the page numbers quoted are from [1].

Using the arrival theorem together with elementary facts regarding integrated tail distributions and length-biased sampling we obtain closed form expressions for the inter-output time and the cycle time distribution in cyclic, single-class Jackson networks. Corresponding expressions for the normalization constant and the throughput are also obtained. c © 2003 Elsevier B.V. All rights reserved.

We present a method for measuring the transverse electric field profile of a beam of light which allows for direct phase retrieval. The measured values correspond, within a normalization constant, to the real and imaginary parts of the electric field in a plane normal to the direction of propagation. This technique represents a self-referencing method for probing the wavefront characteristics o...

We show that with a simple normalization of explanatory variables, marginal effects in probit and logit models simplify dramatically, becoming a function of only the estimated constant term. Related simplifications hold for computation of asymptotic variances of these effects. D 2003 Elsevier B.V. All rights reserved.

We provide a uniformly efficient and simple random variate generator for the entire parameter range of the generalized inverse gaussian distribution. A general algorithm is provided as well that works for all densities that are proportional to a log-concave function φ, even if the normalization constant is not known. It requires only black box access to φ and its derivative.

We first present the top 50 most confident results per dataset, training on the NYU v2 dataset and testing the other dataset. Confidence is the mean value of the weight image (i.e., the normalization constant Z), roughly equivalent to the number of detections, weighted by cablibrated score. We then present results automatically selected among the remaining results, evenly spaced according to co...

The Gaussian process is a useful prior on functions for Bayesian kernel regression and classification. Density estimation with a Gaussian process prior is difficult, however, as densities must be nonnegative and integrate to unity. The statistics community has explored the use of a logistic Gaussian process for density estimation, relying on approximations of the normalization constant (e.g. [1...

URL normalization is a process of transforming URL strings into canonical form. Through this process, duplicate URL representations for web pages can be reduced significantly. There are a number of normalization methods. In this paper, we describe four metrics for evaluating normalization methods. The reliability and consistency of a URL is also considered in our evaluation. With the metrics pr...

In many m~iltidimensional systems, including models of computer and network systems and particle systems, t,he eqnilibrillm distribution of state probabilities anti other performance measl~res hinges on t,he explicit numerical deterrnination of a normalization constant. When the nornializat,ion constant is the a s11n1 of simple, computable functions defined on lattice-points in a constrained sp...

We have selected 42 elliptical galaxies from the literature and estimated their velocity dispersions at the effective radius (σRe) and at 0.54 effective radii (σ0.54Re). We find by a dynamical analysis that the normalized velocity dispersion of the dark halo of an elliptical galaxy σDM is roughly σRe multiplied by a constant, which is almost independent of the core radius or the anisotropy para...