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Anonymous Functions:
The anonymous function is a very easy, one-line function. The benefit of an anonymous function is that it does not have to be stored in an M-file. This can deeply simplify the programs, as often computations are very easy, and the use of anonymous functions decreases the number of M-files essential for a program. The Anonymous functions can be generated in the Command Window or in any script. The format for an anonymous function is as shown below:
fnhandle = @ (arguments) functionbody
here fnhandle stores the function handle; it is necessarily a way of referring to the function. The handle is assigned to this name by using the @ operator. The arguments, in the parentheses, correspond to the argument(s) which are passed to the function, merely like any other type of function. The function body is the body of the function that is any valid MATLAB expression. For illustration, here is an anonymous function which computes and returns the area of a circle:
>> cirarea = @ (radius) pi * radius .^2;
function
num2str function: The num2str function, that converts real numbers, can be called in many ways. If only the real number is passed to the num2str function, it will generate a s
Example of Plotting from a Function: For illustration, the function can be called as shown below: >> y = [1:2:9].^3 y = 1 27 125 343 729
Indexing into Vectors of structures: Frequently, when the data structure is a vector of structures, it is essential to iterate through the vector in order by various fields. F
Dot Product: The dot or inner product of two vectors a and b is written as a • b and is defined as In another words, this is like matrix multiplication when multiplyi
Illustration of Set operations: For illustration, given the vectors as shown below: >> v1 = 2:6 v1 = 2 3 4 5 6 >> v2 = 1:2:7 v2 = 1 3 5 7
Finding products by for loop: an illustration, when 5 is passed to be the value of the input argument n, the function will compute and return 1 + 2 + 3 + 4 + 5, or 15: >> s
Matrix solutions to systems of the linear algebraic equations: The linear algebraic equation is an equation of the form a 1 x 1 + a 2 x 2 + a 3 x 3 . . . . a n x n
Forward substitution: The Forward substitution (done methodically by first getting a 0 in the a 21 place, and then a 31 , and lastly a 32 ): For the Gauss technique,
Scaling: change a row by multiplying it by a non-zero scalar sri → ri For illustration, for the matrix:
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