<p></p><p><font color="#ff0000">外部下载链接：</font></p><p><strong>Rapidshare</strong><br/> </p><p><img alt="" src="http://i39.tinypic.com/io41f5.jpg" border="0"/></p><p><strong>World Scientific      </strong><strong>Amazon</strong></p><p><br/><font size="4">Selected Works Of Kai Lai Chung<br/></font>By <strong>Farid Aitsahlia</strong></p><p><strong>Publisher:</strong>   World Scientific Publishing Company <br/><strong>Number Of Pages:</strong>   844 <br/><strong>Publication Date:</strong>   2008-10-22 <br/><strong>ISBN-10 / ASIN:</strong>   9812833854 <br/><strong>ISBN-13 / EAN:</strong>   9789812833853 </p><p><br/><strong>Product Description:</strong><br/> </p><p>This unique volume presents a collection of the extensive journal publications written by Kai Lai Chung over a span of 70-odd years. It is produced to celebrate his 90th birthday. The selection is only a subset of the many contributions that he has made throughout his prolific career. Another volume, Chance and Choice, published by World Scientific in 2004, contains yet another subset, with four articles in common with this volume. Kai Lai Chung's research contributions have had a major influence on several areas in probability. Among his most significant works are those related to sums of independent random variables, Markov chains, time reversal of Markov processes, probabilistic potential theory, Brownian excursions, and gauge theorems for the Schr??dinger equation. </p><p>As Kai Lai Chung's contributions spawned critical new developments, this volume also contains retrospective and perspective views provided by collaborators and other authors who themselves advanced the areas of probability and mathematics. </p><p>Contents: On Mutually Favorable Events; Fluctuations of Sums of Independent Random Variables; Continuous Parameter Markov Chains; On Last Exit Times; On the Boundary Theory for Markov Chains; Crudely Stationary Counting Processes; Excursions in Brownian Motion; On Stopped Feynman Kac Functionals; The Lifetime of Conditional Brownian Motion in the Plane; Greenian Bounds for Markov Processes; and other papers.</p>

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