logical data type represents true or false states using the numbers 1 and 0, respectively. Certain MATLAB® functions and operators return logical values to indicate fulfillment of a condition. You can use those logical values to index into an array or execute conditional code. For more information, see how to Find Array Elements That Meet a Condition.
Relational operator
Specify the operation for comparing two inputs or determining the signal type of one input.
==~=<<=>=>isInfInfisNaNNaNisFiniter = rem(a,b) returns the remainder after division of a by b, where a is the dividend and b is the divisor.b = mod(a,m) returns the remainder after division of a by m, where a is the dividend and m is the divisor. This function is often called the modulo operation and is computed using b = a - m.*floor(a./m). The mod function follows the convention that mod(a,0) returns a.Y = round(X) rounds each element of X to the nearest integer. In the case of a tie, where an element has a fractional part of exactly 0.5, the round function rounds away from zero to the integer with larger magnitude.Y = ceil(X) rounds each element of X to the nearest integer greater than or equal to that element.Y = fix(X) rounds each element of X to the nearest integer toward zero. For positive X, the behavior of fix is the same as floor. For negative X, the behavior offix is the same as ceil.Y = floor(X) rounds each element of X to the nearest integer less than or equal to that element.S = sum(A) returns the sum of the elements of A along the first array dimension whose size does not equal 1.A is a vector, then sum(A) returns the sum of the elements.A is a matrix, then sum(A) returns a row vector containing the sum of each column.A is a multidimensional array, then sum(A) operates along the first array dimension whose size does not equal 1, treating the elements as vectors. This dimension becomes 1 while the sizes of all other dimensions remain the same.S = sum(A,dim) returns the sum along dimension dim. For example, if A is a matrix, then sum(A,2) is a column vector containing the sum of each row.S = sum(___,outtype) returns the sum with a specified data type, using any of the input arguments in the previous syntaxes. outtype can be 'default','double', or 'native'.S = sum(___,nanflag) specifies whether to include or omit NaN values from the calculation for any of the previous syntaxes. sum(A,'includenan') includes all NaNvalues in the calculation while sum(A,'omitnan') ignores them.A is a vector, then prod(A) returns the product of the elements.A is a nonempty matrix, then prod(A) treats the columns of A as vectors and returns a row vector of the products of each column.A is an empty 0-by-0 matrix, prod(A) returns 1.A is a multidimensional array, then prod(A) acts along the first nonsingleton dimension and returns an array of products. The size of this dimension reduces to 1while the sizes of all other dimensions remain the same.prod computes and returns B as single when the input, A, is single. For all other numeric and logical data types, prod computes and returns B as double.B = prod(A,dim)dim. For example, if A is a matrix, prod(A,2) is a column vector containing the products of each row.B = prod(___,type)type, using any of the input arguments in the previous syntaxes. type can be 'double', 'native', or 'default'.Y = diff(X)X along the first array dimension whose size does not equal 1X is a vector of length m, then Y = diff(X) returns a vector of length m-1. The elements of Y are the differences between adjacent elements of X.X is a nonempty, nonvector p-by-m matrix, then Y = diff(X) returns a matrix of size (p-1)-by-m, whose elements are the differences between the rows of X.X is a 0-by-0 empty matrix, then Y = diff(X) returns a 0-by-0 empty matrix.Y = diff(X,n)diff(X) operator recursively n times. In practice, this means diff(X,2) is the same asdiff(diff(X)).Y = diff(X,n,dim)dim. The dim input is a positive integer scalar.In this section, let us discuss the following basic and commonly used matrix operations:
Addition and Subtraction of Matrices
Division of Matrices
Scalar Operations of Matrices
Transpose of a Matrix
Concatenating Matrices
Matrix Multiplication
Determinant of a Matrix
Inverse of a Matrix
Addition and Subtractions of matrix