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Handbook of Intelligent Computing and Optimization for Sustainable Development


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k.w = k.α + k.βi, where k is a scalar.

      4.4.1 Introduction

Schematic illustration of the complex plane Z(n).

      A matrix is defined in computing science by a set in two dimensions including p × q elements, where p represents the number of rows and q represents the number of columns (cols). A matrix is typically represented by a capital character like M. The element mij is assigned in the place which meets at the ith row and the jth col [5].

      A matrix with p = 1 is referred to as a row matrix, while one with q = 1 is referred to as “a column matrix”. A matrix with p = q is referred to as “a square matrix” and its elements m11, m22, ----, mqq is referred to as “a main diagonal”. A matrix having all rows and cols which put to 0’s is referred as “an additive identity matrix” and the letter 0 is used to represent it. A square one having 1’s on “the main diagonal” and 0’s somewhere else is referred to as “an identity matrix” and the letter I is used to represent it [5].

      If two matrices have the identical number of rows and columns and their corresponding elements are identical, then they are identical. In terms of representation of letters, M = N if they have mij = nij for all is and js [5].

      4.4.2 Matrix Arithmetic Operations

      It may be to add and subtract two matrices with the equal number of rows and cols. R = M + N means “addition of two matrices”, M and N. In this case, rij = mij + nij. R = MN means “subtraction of two matrices”, M and N. In this case, rij = mijnij [5].

      If the quantity of cols in the matrix is identical to the quantity of rows in another matrix, then the two matrices can be multiplied. In this case, if M is a matrix with p × k and N is one with k × q, “the product matrix” of them is a matrix R with p × q. Each element of “the product matrixR is considered in the way rij = ∑mik × nkj [5].

      “Scalar multiplication of a matrix” is defined by multiplying a matrix with a scalar number. If M is a matrix with p × q and β is a scalar number, then R = β × M is a matrix with p × q. In this case, rij = β × mij for each element of the matrix R [5].

      4.4.3 Inverses

      Determinant. “The determinant of an equivalent matrix” defined as det(M) for M of size q × q can be designed recursively as given below [5].

       • If q = 1, det(M) = m11.

       • If q > 1, .

      where Mij stands for a matrix M defined by ith row and jth column. The determinant may be found only for an equivalent matrix.

      Additive Inverse. If matrix N is “the additive inverse” of matrix M, then M + N = 0 because their corresponding elements have the property: nij = −mij for all is and js. The symbol –M is generally used to represent the additive inverse of matrix M [5].

      Multiplicative Inverse. Only square matrices can be used to compute “the reciprocal of a matrix”. Matrix M has a reciprocal of N, resulting in M × N = N × M = I. The symbol M-1 is generally used to represent a reciprocal of M. The matrices have their reciprocals in the case of det(M) ≠ 0 [5].

      4.5.1 Introduction

      The “elliptic curve” in a finite field known as E(GF) is a curve in cubic-form derived from the Weierstrass equation: y2 + β1xy + β3y = x3 + β2x2 + β4x + β6 in GF. In this case, βiGF and GF is a finite field [4].

      The curve E(GF(p)) has the form: y2 = x3 + ax + b in which p is a prime greater than 3, a, bGF(p) and 4a3 + 27b2 ≠ 0. (β1 = β2 = β3 = 0; β4 = a and β6 = b on the Weierstrass equation) [4].

      4.5.2 Arithmetic Operations on E(GF(p))

Graph depicts about adding the points P equals to M plus N. Graph depicts about doubling a point P equals M plus M.

      The algebraic methods for adding points and doubling a point on E(GF(p)) are followings [4].

       • M + O = O + M = M and M + (−M) = O for any point, M ∈ E(GF(p)). If M = (x, y) ∈ E(GF(p)), then (x, −y) is defined as (−M) which stands for the inverse of M. O is the point at infinity which is known as additive identity.

       • (Adding points). Consider that M, N ∈ E(GF(p)), M = (x1, y1), and N = (x2,