
Exercises for Unit I V (The basic number systems of mathematics)
... The so – called sequence of Fibonacci numbers is given recursively by the formulas F0 = F1 = 1 and Fn = F n – 1 + F n – 2 for n > 1. Find a function H as in the recursive definition theorem which can be used to define the sequence of Fibonacci numbers. [ Hint : The cases n = 1 and n > 1 must be hand ...
... The so – called sequence of Fibonacci numbers is given recursively by the formulas F0 = F1 = 1 and Fn = F n – 1 + F n – 2 for n > 1. Find a function H as in the recursive definition theorem which can be used to define the sequence of Fibonacci numbers. [ Hint : The cases n = 1 and n > 1 must be hand ...
Calculus Pretest
... IX. Represent Geometric Parameters with Algebraic Expressions 1. The length of a rectangle is 3 meters more than twice its width. What is the width if the perimeter of the rectangle is 186 meters? 2. A square picture is mounted on a larger rectangular sheet of poster paper leaving a border around th ...
... IX. Represent Geometric Parameters with Algebraic Expressions 1. The length of a rectangle is 3 meters more than twice its width. What is the width if the perimeter of the rectangle is 186 meters? 2. A square picture is mounted on a larger rectangular sheet of poster paper leaving a border around th ...
Mastery Test 1 Study Guide
... Counting #’s: 1, 2, 3,…. Whole #’s: 0, 1, 2, 3,…. Integers: …., -3, -2, -1, 0, 1, 2, 3,…. Positive #’s: all numbers greater than 0 Negative #’s: all numbers less than 0 Rational #’s: all Numbers that are NOT IRRATIONAL Irrational #’s: CRAZY, most well know example is Pi (3.1416……..) #’ ...
... Counting #’s: 1, 2, 3,…. Whole #’s: 0, 1, 2, 3,…. Integers: …., -3, -2, -1, 0, 1, 2, 3,…. Positive #’s: all numbers greater than 0 Negative #’s: all numbers less than 0 Rational #’s: all Numbers that are NOT IRRATIONAL Irrational #’s: CRAZY, most well know example is Pi (3.1416……..) #’ ...
Factors Factors are numbers that are multiplied to produce a specific
... To solve an equation, isolate the variable on one side of the equal sign. When undoing the operations performed on the variable, follow the reverse order of operations: • subtract and add • multiply and divide 5x + 7 = 22 5x + 7 − 7 = 22 – 7 Reverse the addition of 7 by subtracting 7. 5x = 15 5x = 1 ...
... To solve an equation, isolate the variable on one side of the equal sign. When undoing the operations performed on the variable, follow the reverse order of operations: • subtract and add • multiply and divide 5x + 7 = 22 5x + 7 − 7 = 22 – 7 Reverse the addition of 7 by subtracting 7. 5x = 15 5x = 1 ...
PDF
... numbers x and y which are not congruent modulo n with x not congruent to −y modulo n but have x2 ≡ y 2 (mod n). If two such numbers are found, one can then say that (x + y)(x − y) ≡ 0 (mod n). Then, x + y and x − y must have non-trivial factors in common with n. The quadratic sieve method of factori ...
... numbers x and y which are not congruent modulo n with x not congruent to −y modulo n but have x2 ≡ y 2 (mod n). If two such numbers are found, one can then say that (x + y)(x − y) ≡ 0 (mod n). Then, x + y and x − y must have non-trivial factors in common with n. The quadratic sieve method of factori ...
On the Reducibility of Cyclotomic Polynomials over Finite Fields
... A polynomial f ∈ Q[x] that is irreducible over Q may still factor into smaller degree polynomials over Z/pZ for some prime p. For example, let f (x) = x4 + 1. It can easily be shown that f is irreducible over Q using Eisenstein’s Criterion [7, pgs. 23-24]. Yet over Z/2Z, f is reducible, since x4 +1 ...
... A polynomial f ∈ Q[x] that is irreducible over Q may still factor into smaller degree polynomials over Z/pZ for some prime p. For example, let f (x) = x4 + 1. It can easily be shown that f is irreducible over Q using Eisenstein’s Criterion [7, pgs. 23-24]. Yet over Z/2Z, f is reducible, since x4 +1 ...
Factorization
In mathematics, factorization (also factorisation in some forms of British English) or factoring is the decomposition of an object (for example, a number, a polynomial, or a matrix) into a product of other objects, or factors, which when multiplied together give the original. For example, the number 15 factors into primes as 3 × 5, and the polynomial x2 − 4 factors as (x − 2)(x + 2). In all cases, a product of simpler objects is obtained.The aim of factoring is usually to reduce something to “basic building blocks”, such as numbers to prime numbers, or polynomials to irreducible polynomials. Factoring integers is covered by the fundamental theorem of arithmetic and factoring polynomials by the fundamental theorem of algebra. Viète's formulas relate the coefficients of a polynomial to its roots.The opposite of polynomial factorization is expansion, the multiplying together of polynomial factors to an “expanded” polynomial, written as just a sum of terms.Integer factorization for large integers appears to be a difficult problem. There is no known method to carry it out quickly. Its complexity is the basis of the assumed security of some public key cryptography algorithms, such as RSA.A matrix can also be factorized into a product of matrices of special types, for an application in which that form is convenient. One major example of this uses an orthogonal or unitary matrix, and a triangular matrix. There are different types: QR decomposition, LQ, QL, RQ, RZ.Another example is the factorization of a function as the composition of other functions having certain properties; for example, every function can be viewed as the composition of a surjective function with an injective function. This situation is generalized by factorization systems.