/* * Starter file for Week 2 Question 2. * * Created for COMP20007 Design of Algorithms 2020 * Template written by Tobias Edwards * Updated 20210308 by Grady Fitzpatrick * Implementation by YOUR NAME HERE. */ #include #include /* * Recall, these are called function prototypes and they declare the function * names, argument […]
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COMP20007 Design of Algorithms B-trees Daniel Beck Lecture 15 Semester 1, 2021 1 Primary vs. Secondary Memories • Primary memory (RAM) 2 Primary vs. Secondary Memories • Primary memory (RAM) • Key comparisons are the most significant operation. • The paradigm we’ve seen so far. 2 Primary vs. Secondary Memories • Primary memory (RAM) •
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COMP20007 Design of Algorithms Growth Rate and Algorithm Efficiency Lars Kulik Lecture 3 Semester 1, 2021 1 Assessing Algorithm “Efficiency” Resources consumed: time and space. We want to assess efficiency as a function of input size: • Mathematical vs empirical assessment • Average case vs worst case Knowledge about input peculiarities may affect the choice
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COMP20007 Design of Algorithms Input Enhancement Part 1: Distribution Sorting Daniel Beck Lecture 17 Semester 1, 2020 1 Simple Distribution Sort 1406532 2 Simple Distribution Sort Looks Θ(n) even in worst case! Is it really? 1406532 2 Simple Distribution Sort 10 41 02 64 53 39 27 3 Simple Distribution Sort Θ(n + k) worst
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Tutorial COMP20007 Design of Algorithms Week 11 Workshop Solutions 1. Counting Sort To perform counting sort we note that the range of possible input characters are a, b, c, d, e, and f . We then loop through the array and tally the frequencies of each character: abcdef [522101] We then read these frequencies in
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[Content_Types].xml _rels/.rels matlab/document.xml matlab/output.xml metadata/coreProperties.xml metadata/mwcoreProperties.xml metadata/mwcorePropertiesExtension.xml metadata/mwcorePropertiesReleaseInfo.xml The Finite Difference Method for Solving Boundary Value Problems In this livescript, you will learn how To solve boundary value problems using finite difference methods. We’ll continue with our example on steady one dimensional heat diffusion \frac{d^{2}T}{dx^{2}}=0 with the boundary conditions T(0)=0 and T(1)=1 . The process
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Tutorial COMP20007 Design of Algorithms Week 10 Workshop Solutions 1. Separate chaining Here’s the hash table after inserting the keys according to the hash function h(k)=k modLwithL=2: 0 6→12→8 1 17→11→21→33→5→23→1→9 In terms of better data structures over a standard linked list, there are plenty of options to try. • A move-to-front (MTF) list could
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clear all clear all; Delta=0.2; x=1:Delta:2; alpha=5.0; beta=3.0; n=length(x)-1; A=zeros(n-1,n-1); C=zeros(n-1,1); ysol=zeros(size(x)); A(1,1)=-(2/Delta.^2)-2./(x(2).^2); A(1,2)=(1/Delta.^2)+(2./x(2))*(1/(2*Delta)); for i=2:n-2 A(i,i-1)=(1/Delta.^2)-(2./x(i+1))*(1/(2*Delta)); A(i,i)=-(2/Delta.^2)-2./(x(i+1).^2); A(i,i+1)=(1/Delta.^2)+(2./x(i+1))*(1/(2*Delta)); end A(n-1,n-2)=(1/Delta.^2)-(2./x(n))*(1/(2*Delta)); A(n-1,n-1)=-(2/Delta.^2)-2./(x(n).^2); C(1)=-alpha*((1/Delta.^2)-(2./x(2))*(1/(2*Delta))); C(n-1)=-beta*((1/Delta.^2)+(2./x(n))*(1/(2*Delta))); % % This is a very inefficient way of solving this system of equations % Matrix [A] has got lots of zeros % Should use Thomas algorithm and not store all
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