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Strong Induction
There are occasions where the , at least as we have studied it up to this point, does not seem sufficient. Here is a concrete example.
Strong Induction
There are occasions where the , at least as we have studied it up to this point, does not seem sufficient. Here is a concrete example. The professor asked Bob to study a function \(f(n)\) defined recursively by \(f(n) = 2f(n-1) - f(n-2)\) with \(f(1)=3\) and \(f(2)=5\). Specifically, the professor asked Bob to compute \(f(10^{10})\), which seems like a daunting task. Over coffee, Bob scribbled on a napkin and determined that \(f(3)=7\) and \(f(4)=9\), and on the basis of these calculations alone, he thought that it might just be possible that \(f(n) = 2n+1\) for all \(n\geq 1\). If this were true, he could simply report that \(f(10^{10})=2\cdot 10^{10}+1=20000000001\).
Bob was beginning to understand proofs by induction, so he tried to prove that \(f(n)=2n+1\) for all \(n\ge1\) by induction. For the base step, he noted that \(f(1)= 3=2\cdot1+1\), so all is ok to this point. For the inductive step, he assumed that \(f(k)=2k+1\) for some \(k\ge1\) and then tried to prove that \(f(k+1)=2(k+1)+1\). If this step could be completed, then the proof by induction would be done.
But at this point, Bob seemed to hit a barrier, because \[\begin{aligned}\end{aligned}\] using the inductive hypothesis to replace \(f(k)\) by \(2k+1\). However, he's was totally perplexed about what to do with the \(f(k-1)\). If he knew that \(f(k-1)=2(k-1)+1\), then the right hand side would result in \(2(2k+1) -(2k-1)= 2k+3=2(k+1)+1\), which is exactly what he wants. Bob always plays by the rules, and he has to admit that he doesn't know that \(f(k-1)=2(k-1)+1\). He only knows that \(f(k)=2k+1\).
Bob was about to throw in the towel and ask his computer to start making the calculations recursively, when Carlos comes along and asks what he's doing. Carlos sees right away that the approach Bob was taking to prove that \(f(n)=2n+1\) by induction won't workbut after a moment's reflection, Carlos says that there's a stronger form of an inductive proof that will do the trick. Carlos patiently explained to Bob a proposition which is called the Strong Principle of Mathematical Induction. To prove that an open statement \(S_n\) is valid for all \(n\ge1\), it is enough to
Show that \(S_1\) is valid, and
Show that \(S_{k+1}\) is valid whenever \(S_m\) is valid for all integers \(m\) with \(1\le m\le k\).
The validity of this proposition is trivial since it is stronger than the principle of induction. What is novel here is that in order to prove a statement, it is sometimes to your advantage to prove something even stronger. Combinatorial mathematicians call this the bootstrap phenomenon.
Condensed: the full section is in Keller & Trotter, Applied Combinatorics.
Haddaad Ma jiro xisaabis oo ku nool midkan, laakiin qaybaha ka mid ah waa la xisaabi karaa. Ku raaxayso mid ka hooseeya, ama ku qor adiga kuu gaar ah.
A xisaab bilaash ah oo ku daray qoraalada waxbarasho kasta, diiwaanka waxa aad dhamaatay, dhibaatooyinka aad xal u tahay meel kaliya, iyo macallinka aad weydiisan kartaa oo ku saabsan bogga. Xisaabta oo keliya waa u furan yahay qof kasta, la diiwaan geliyey ama aan.
Ku soo biir Ku soo galCalaamadaha la isticmaalay halkan
Taab calaamad kasta oo loogu talagalay qeexidda buuxda, sawir, iyo waxa xarfaha oo dhan ka mid ah ka dhigan tahay.
Su'aalaha dadku waydiiyaan
Permutation or combination?
Ask whether order matters. A lock code is a permutation (order matters); a hand of cards is a combination (it does not).
What is a graph in this sense?
Dots (vertices) joined by lines (edges), not a plot. Road maps, social networks and molecules are graphs; questions like "is there a route" and "how few colours" are graph theory.
Qaybaha ee boggaan waxaa la beddelay ka Keller & Trotter, Applied Combinatorics (CC BY-SA 4.0). Condensed iyo dib-oo halkan lagu sharaxay; khaladaadka waa inoo.
In ka badan Combinatorics & Graph Theory
The counting principlesPigeonhole principle and inclusion, exclusionBinomial coefficients and Pascal's triangleRecurrences and generating functionsGraphs: vertices, edges, degreesPaths, cycles, trees, Euler and HamiltonColouring and planar graphs