Numerical Analysis
Hi, I was wondering if there is anyone who can perform numerical analysis and write a code when required. Thanks
In differentiated-goods duopoly business, with inverse demand curves: P1 = 10 – 5Q1 – 2Q2P2 = 10 – 5Q2 – 2Q1 and per unit costs for each and every firm equal to 1.<
Measuring complexity: Many algorithms have an integer n, or two integers m and n, as input - e.g., addition, multiplication, exponentiation, factorisation and primality testing. When we want to describe or analyse the `easiness' or `hardness' of the a
Factorisation by Fermat's method: This method, dating from 1643, depends on a simple and standard algebraic identity. Fermat's observation is that if we wish to nd two factors of n, it is enough if we can express n as the difference of two squares.
Wffs (Well-formed formulas): These are defined inductively by the following clauses: (i) If P is an n-ary predicate and t1, …, tn are terms, then P(t1, …, t
For every value of real GDP, actual investment equals
An office of state license bureau has two types of arrivals. Individuals interested in purchasing new plates are characterized to have inter-arrival times distributed as EXPO(6.8) and service times as TRIA(808, 13.7, 15.2); all times are in minutes. Individuals who want to renew or apply for a new d
Using the PairOfDice class design and implement a class to play a game called Pig. In this game the user competes against the computer. On each turn the player rolls a pair of dice and adds up his or her points. Whoever reaches 100 points first, wins. If a player rolls a 1, he or she loses all point
The function is clearly undefined at , but despite all of this the function does have a limit as approaches 0. a) Use MATLAB and ezplot to sketch for , and use the zoom on facility to guess the . You need to include you M-file, outp
integral e^(-t)*e^(tz) t between 0 and infinity for Re(z)<1
The big-O hierarchy: A few basic facts about the big-O behaviour of some familiar functions are very important. Let p(n) be a polynomial in n (of any degree). Then logbn is O(p(n)) and p(n) is O(an<
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