𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Rate of Convergence of the Discrete Pólya-1 Algorithm

✍ Scribed by A.G. Egger; G.D. Taylor


Publisher
Elsevier Science
Year
1993
Tongue
English
Weight
389 KB
Volume
75
Category
Article
ISSN
0021-9045

No coin nor oath required. For personal study only.

✦ Synopsis


The rate of convergence of the discrete Polya-1 algorithm is studied. Examples are given to show that the rates derived are sharp. (c) 1993 Academic Press, Inc


📜 SIMILAR VOLUMES


The differentiability of Pólya's functio
✍ Peter D Lax 📂 Article 📅 1973 🏛 Elsevier Science 🌐 English ⚖ 304 KB

In his paper [l] P6lya defines the following function P, mapping the interval [0, I] onto a right triangle T. Let t be any number in the unit interval; expand it into a binary fraction: t = .d,d, ... The n-th digit d,(t) of t is either 0 or 1. For each t we assign a sequence of nested triangles T

Techniques for bounding the convergence
✍ Yuri Rabinovich; Avi Wigderson 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 308 KB 👁 2 views

The main purpose of the present paper is the study of computational aspects, ## Ž . and primarily the convergence rate, of genetic algorithms GAs . Despite the fact that such algorithms are widely used in practice, little is known so far about their theoretical properties, and in particular about

Effects of Asynchronism on the Convergen
✍ Aydin Üresin; Michel Dubois 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 392 KB

In multiprocessor systems, iterative algorithms can be implemented synchronously or asynchronously. Unfortunately, few guidelines exist to make a choice. In this paper, we compare the execution times of an asynchronous iterative algorithm and of its synchronous counterpart. Synchronization overhead

Robustness and convergence rate of a dis
✍ Samer S. Saab 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 127 KB 👁 2 views

In this paper, we apply a discrete-time learning algorithm to a class of discrete-time varying nonlinear systems with a$ne input action and linear output having relative degree one. We investigate the robustness of the algorithm to state disturbance, measurement noise and reinitialization errors. We