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		<summary type="html">&lt;p&gt;193.136.24.142: /* Definition */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;{{no footnotes|date=February 2013}}&lt;br /&gt;
In [[computer science]], the &#039;&#039;&#039;Akra–Bazzi method&#039;&#039;&#039;, or &#039;&#039;&#039;Akra–Bazzi theorem&#039;&#039;&#039;, is used to analyze the asymptotic behavior of the mathematical [[recurrence relation|recurrences]] that appear in the analysis of [[divide and conquer algorithm|divide and conquer]] [[algorithm]]s where the sub-problems have substantially different sizes.  It is a generalization of the well-known [[master theorem]], which assumes that the sub-problems have equal size.&lt;br /&gt;
&lt;br /&gt;
== The formula ==&lt;br /&gt;
The Akra–Bazzi method applies to recurrence formulas of the form&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;T(x)=g(x) + \sum_{i=1}^k a_i T(b_i x + h_i(x))\qquad \text{for }x \geq x_0.&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
The conditions for usage are:&lt;br /&gt;
&lt;br /&gt;
* sufficient base cases are provided&lt;br /&gt;
* &amp;lt;math&amp;gt;a_i&amp;lt;/math&amp;gt; and &amp;lt;math&amp;gt;b_i&amp;lt;/math&amp;gt; are constants for all i&lt;br /&gt;
* &amp;lt;math&amp;gt;a_i &amp;gt; 0&amp;lt;/math&amp;gt; for all i&lt;br /&gt;
* &amp;lt;math&amp;gt;0 &amp;lt; b_i &amp;lt; 1&amp;lt;/math&amp;gt; for all i&lt;br /&gt;
* &amp;lt;math&amp;gt;\left|g(x)\right| \in O(x^c)&amp;lt;/math&amp;gt;, where &#039;&#039;c&#039;&#039; is a constant and &#039;&#039;O&#039;&#039; notates [[Big O notation]]&lt;br /&gt;
* &amp;lt;math&amp;gt;\left| h_i(x) \right| \in O\left(\frac{x}{(\log x)^2}\right)&amp;lt;/math&amp;gt; for all i&lt;br /&gt;
* &amp;lt;math&amp;gt;x_0&amp;lt;/math&amp;gt; is a constant&lt;br /&gt;
&lt;br /&gt;
The asymptotic behavior of T(x) is found by determining the value of p for which &amp;lt;math&amp;gt;\sum_{i=1}^k a_i b_i^p = 1&amp;lt;/math&amp;gt; and plugging that value into the equation&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;T(x) \in \Theta \left( x^p\left( 1+\int_1^x \frac{g(u)}{u^{p+1}}du \right)\right)&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
(see [[Big O notation|Θ]]). Intuitively, &amp;lt;math&amp;gt;h_i(x)&amp;lt;/math&amp;gt; represents a small perturbation in the index of T.  By noting that &amp;lt;math&amp;gt;\lfloor b_i x \rfloor = b_i x + (\lfloor b_i x \rfloor - b_i x)&amp;lt;/math&amp;gt; and that &amp;lt;math&amp;gt;\lfloor b_i x \rfloor - b_i x&amp;lt;/math&amp;gt; is always between 0 and 1, &amp;lt;math&amp;gt;h_i(x)&amp;lt;/math&amp;gt; can be used to ignore the [[floor function]] in the index.  Similarly, one can also ignore the [[ceiling function]].  For example, &amp;lt;math&amp;gt;T(n) = n + T \left(\frac{1}{2} n \right)&amp;lt;/math&amp;gt; and &amp;lt;math&amp;gt;T(n) = n + T \left(\left\lfloor \frac{1}{2} n \right\rfloor \right)&amp;lt;/math&amp;gt; will, as per the Akra–Bazzi theorem, have the same asymptotic behavior.&lt;br /&gt;
&lt;br /&gt;
== An example ==&lt;br /&gt;
Suppose &amp;lt;math&amp;gt;T(n)&amp;lt;/math&amp;gt; is defined as 1 for integers &amp;lt;math&amp;gt;0 \leq n \leq 3&amp;lt;/math&amp;gt; and &amp;lt;math&amp;gt;n^2 + \frac{7}{4} T \left( \left\lfloor \frac{1}{2} n \right\rfloor \right) + T \left( \left\lceil \frac{3}{4} n \right\rceil \right)&amp;lt;/math&amp;gt; for integers &amp;lt;math&amp;gt;n &amp;gt; 3&amp;lt;/math&amp;gt;.  In applying the Akra–Bazzi method, the first step is to find the value of p for which &amp;lt;math&amp;gt;\frac{7}{4} \left(\frac{1}{2}\right)^p + \left(\frac{3}{4} \right)^p = 1&amp;lt;/math&amp;gt;.  In this example, &#039;&#039;p&#039;&#039;&amp;amp;nbsp;=&amp;amp;nbsp;2.  Then, using the formula, the asymptotic behavior can be determined as follows:&lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;&lt;br /&gt;
\begin{align}&lt;br /&gt;
T(x) &amp;amp; \in \Theta \left( x^p\left( 1+\int_1^x \frac{g(u)}{u^{p+1}}\,du \right)\right) \\&lt;br /&gt;
&amp;amp; = \Theta \left( x^2 \left( 1+\int_1^x \frac{u^2}{u^3}\,du \right)\right) \\&lt;br /&gt;
&amp;amp; = \Theta(x^2(1 + \ln x)) \\&lt;br /&gt;
&amp;amp; = \Theta(x^2 \log x).&lt;br /&gt;
\end{align}&lt;br /&gt;
&amp;lt;/math&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Significance ==&lt;br /&gt;
The Akra–Bazzi method is more useful than most other techniques for determining asymptotic behavior because it covers such a wide variety of cases.  Its primary application is the approximation of the [[Run time (program lifecycle phase)|runtime]] of many divide-and-conquer algorithms.  For example, in the [[merge sort]], the number of comparisons required in the worst case, which is roughly proportional to its runtime, is given recursively as &amp;lt;math&amp;gt;T(1) = 0&amp;lt;/math&amp;gt; and &lt;br /&gt;
&lt;br /&gt;
:&amp;lt;math&amp;gt;T(n) = T\left(\left\lfloor \frac{1}{2} n \right\rfloor \right) + T\left(\left\lceil \frac{1}{2} n \right\rceil \right) + n - 1&amp;lt;/math&amp;gt; &lt;br /&gt;
&lt;br /&gt;
for integers &amp;lt;math&amp;gt;n &amp;gt; 0&amp;lt;/math&amp;gt;, and can thus be computed using the Akra–Bazzi method to be &amp;lt;math&amp;gt;\Theta(n \log n)&amp;lt;/math&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
*Mohamad Akra, Louay Bazzi: On the solution of linear recurrence equations. &#039;&#039;Computational Optimization and Applications&#039;&#039; &#039;&#039;&#039;10&#039;&#039;&#039;(2):195&amp;amp;ndash;210, 1998.&lt;br /&gt;
*Tom Leighton: [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.39.1636 Notes on Better Master Theorems for Divide-and-Conquer Recurrences], Manuscript. Massachusetts Institute of Technology, 1996, 9 pages.&lt;br /&gt;
*[http://www.mpi-inf.mpg.de/~mehlhorn/DatAlg2008/NewMasterTheorem.pdf Proof and application on few examples]&lt;br /&gt;
&lt;br /&gt;
{{DEFAULTSORT:Akra-Bazzi Method}}&lt;br /&gt;
[[Category:Asymptotic analysis]]&lt;br /&gt;
[[Category:Theorems in discrete mathematics]]&lt;br /&gt;
[[Category:Recurrence relations]]&lt;br /&gt;
[[Category:Bazzi family]]&lt;/div&gt;</summary>
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