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severity, exposure and probability
A strictly lower triangular matrix is a kind of (lower) triangular matrix. Term "lower" implies matrix has elements only in the lower half. The condition "strictly" implies that even the "diagonal" of such lower triangular matrix is populated with '0's. The strictly lower triangular matrix thus has '0's in its diagonal as well as the upper triangle part. In other words, a strictly lower triangular matrix is a lower triangular matrix minus its diagonal.
the order is m p and the matrices can be multiplied if and only if the first one (matrix A) has the same number of columns as the second one (matrix B) has rows i.e)is Matrix A has n columns, then Matrix B MUST have n rows.Equal Matrix: Two matrices A=|Aij| and B=|Bij| are said to be equal (A=B) if and only if they have the same order and each elements of one is equal to the corresponding elements of the other. Such as A=|1 2 3|, B=|1 2 3|. Thus two matrices are equal if and only if one is a duplicate of the other.
Using sparse matrices to store data that contains a large number of zero-valued elements can both save a significant amount of memory and speed up the processing of that data. sparse is an attribute that you can assign to any two-dimensional MATLAB matrix that is composed of double or logical elements.The sparse attribute allows MATLAB to:Store only the nonzero elements of the matrix, together with their indices.Reduce computation time by eliminating operations on zero elements.For full matrices, MATLAB stores every matrix element internally. Zero-valued elements require the same amount of storage space as any other matrix element. For sparse matrices, however, MATLAB stores only the nonzero elements and their indices. For large matrices with a high percentage of zero-valued elements, this scheme significantly reduces the amount of memory required for data storage.
Vector matrix has both size and direction. There are different types of matrix namely the scalar matrix, the symmetric matrix, the square matrix and the column matrix.
reduction
Severity, Exposure, and Probability.
Severity, Exposure, and Probability.
Severity, Exposure, and Probability.
severity, exposure, and probability
Severity, Exposure, and Probability.
Severity, Exposure, and Probability.
severity, exposure, and probability
severity, exposure, and probability
Severity, Exposure, and Probability.
reduction
in assessing hazards which elements make up the cross matrix comparison to determine a risk level