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Fix content error
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@ -155,7 +155,7 @@ Small-o, commonly written as **o**, is an Asymptotic Notation to denote the
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upper bound (that is not asymptotically tight) on the growth rate of runtime
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upper bound (that is not asymptotically tight) on the growth rate of runtime
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of an algorithm.
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of an algorithm.
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`f(n)` is o(g(n)), if for some real constants c (c > 0) and n<sub>0</sub> (n<sub>0</sub> > 0), `f(n)` is < `c g(n)`
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`f(n)` is o(g(n)), if for all real constants c (c > 0) and n<sub>0</sub> (n<sub>0</sub> > 0), `f(n)` is < `c g(n)`
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for every input size n (n > n<sub>0</sub>).
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for every input size n (n > n<sub>0</sub>).
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The definitions of O-notation and o-notation are similar. The main difference
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The definitions of O-notation and o-notation are similar. The main difference
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@ -168,7 +168,7 @@ Small-omega, commonly written as **ω**, is an Asymptotic Notation to denote
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the lower bound (that is not asymptotically tight) on the growth rate of
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the lower bound (that is not asymptotically tight) on the growth rate of
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runtime of an algorithm.
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runtime of an algorithm.
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`f(n)` is ω(g(n)), if for some real constants c (c > 0) and n<sub>0</sub> (n<sub>0</sub> > 0), `f(n)` is > `c g(n)`
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`f(n)` is ω(g(n)), if for all real constants c (c > 0) and n<sub>0</sub> (n<sub>0</sub> > 0), `f(n)` is > `c g(n)`
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for every input size n (n > n<sub>0</sub>).
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for every input size n (n > n<sub>0</sub>).
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The definitions of Ω-notation and ω-notation are similar. The main difference
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The definitions of Ω-notation and ω-notation are similar. The main difference
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