Let us consider a constant "a" which is greater than zero and an exp function of the type f(n) = a^n. are there two functions of the same type wiht diff "a" but they grow at an equal rate? give proof as well
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Let us consider a constant "a" which is greater than zero and an exp function of the type f(n) = a^n. are there two functions of the same type wiht diff "a" but they grow at an equal rate? give proof as well
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- How do we define that a function f(n) has an upper bound g(n), i.e., f(n) ∈ O(g(n))?Consider the function f : N × N → N given byf(m, n) = 2m-1(2n − 1), (m, n) ∈ N × NShow that f is bijectiveWrite a function linear_independence that takes a collection of vectors with integer entries (each written as a list), and returns True if this collection of vectors is linearly independent, and False otherwise. Examples: linear_independence([1,2]) should return True. linear_independence([1,3,7],[2,8,3],[7,8,1]) should returnTrue. linear_independence([1,3,7],[2,8,3],[7,8,1],[1,2,3]) should return False.
- PLEASE HELP ME. kindly show all your work 1. Prove that∀k ∈ N, 1k + 2k + · · · + nk ∈ Θ(nk+1). 2. Suppose that the functions f1, f2, g1, g2 : N → R≥0 are such that f1 ∈ Θ(g1) and f2 ∈ Θ(g2).Prove that (f1 + f2) ∈ Θ(max{g1, g2}). Here (f1 + f2)(n) = f1(n) + f2(n) and max{g1, g2}(n) = max{g1(n), g2(n)}. 3. Let n ∈ N \ {0}. Describe the largest set of values n for which you think 2n < n!. Use induction toprove that your description is correct.Here m! stands for m factorial, the product of first m positive integers. 4. Prove that log2 n! ∈ O(n log2 n). Thank you. But please show all work and all stepsLet Σn denote the set of all binary strings with lengths less than n. For example, Σ2 = {λ, 0, 1} and Σ3 = {λ, 0, 1, 00, 01, 10, 11} where λ is the empty string, i.e. the string of length 0. For x ∈ Σ we denote the length of x by |x|. a) How many functions f : Σn → Σn are there? b) How many one-to-one functions f : Σn → Σn are there?Given g = {(1,c),(2,a),(3,d)}, a function from X = {1,2,3} to Y = {a,b,c,d}, and f = {(a,r),(b,p),(c,δ),(d,r)}, a function from Y to Z = {p, β, r, δ}, write f o g as a set of ordered pairs.
- Give a clear description of an efficient algorithm for finding the k smallest elements of a very large n-element vector. Compare its running time with that of other plausible ways of achieving the same result, including that of applying k times your solution for part (a). [Note that in part (a) the result of the function consists of one element, whereas here it consists of k elements. As above, you may assume for simplicity that all the elements of the vector are different.]Consider the following for loops in R. For each for loop, list the values (in order) that the variable i takes on in the body of the loop. Briefly (in no more than a few sentences) explain why. a) for(i in 1+2:3.4*5) { } b) for(i in dim(matrix(0, nr = 7, nc = 8))) { } c) for(i in rnorm(3)) { } d) for(i in iris[1:3,3]) { } e) for(j in c(1, 2, 3, 4, 5)) { } f) for(i in (function(x) x*x)(c(1, 2, 3))) { } g) for(i in NULL) { } h) for(i in strsplit(as.character(4*atan(1)),’’) [[1]][1:10]) { }Give an example of a function f(n) such that f(n) ∈ O(n √ n) and f(n) ∈ Ω(n log n)) but f(n) ∈/ Θ(n √ n) and f(n) ∈/ Θ(n log n)). 2. Prove that if f(n) ∈ O(g(n)) and f(n) ∈ O(h(n)), then f(n) ^2 ∈ O(g(n) × h(n)). 3. By using the definition of Θ prove that 4√ 7n^3 − 6n^2 + 5n − 3 ∈ Θ(n 1.5 )
- Give a program P such that for any n > 0 and every computation s1 = (1, σ), s2, ..., sk of P that has the equation X = n in σ, k = 4n + 2.Make a program in Phyton that show the perform function evaluations for Hermite polynomials based on series expressions on variousorder n and the variable x. Try to compare the results of the evaluation with the results of the evaluation Hermite polynomials based on recurrence relations, especially when n and x are largePlease help me with these question. SHow all you work. Thank you 1. Prove that∀k ∈ N, 1k + 2k + · · · + nk ∈ Θ(nk+1). 2. Suppose that the functions f1, f2, g1, g2 : N → R≥0 are such that f1 ∈ Θ(g1) and f2 ∈ Θ(g2).Prove that (f1 + f2) ∈ Θ(max{g1, g2}).Here (f1 + f2)(n) = f1(n) + f2(n) and max{g1, g2}(n) = max{g1(n), g2(n)}