By Stormy Attaway
Assuming no wisdom of programming, this e-book offers either programming innovations and MATLAB’s integrated capabilities, offering an ideal platform for exploiting MATLAB’s vast features for tackling engineering difficulties. It starts off with programming suggestions corresponding to variables, assignments, input/output, and choice statements, strikes onto loops after which solves difficulties utilizing either the ‘programming concept’ and the ‘power of MATLAB’ side-by-side. In-depth insurance is given to input/output, a subject that's basic to many engineering applications.
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Additional info for Matlab: A Practical Introduction to Programming and Problem Solving
The logarithm base y of a number x is the power of y that will produce the number x. 653 is 45. The base of a logarithm can be any number, but we will typically use either base 10 or base 2 in our analysis. We will use log as shorthand for log10 and lg as shorthand for log2. Logarithms are a strictly increasing function. This means that given two numbers X and Y, if X > Y, logB X > logB Y for all bases B. Logarithms are one-to-one functions. This means that if logB X = logB Y, X = Y. 3 MATHEMATICAL BACKGROUND 15 These properties can be combined to help simplify a function.
The tree for a list of three elements is shown in Fig. 4. Trees of this form are called decision trees. Each sort algorithm produces a different decision tree based on the elements that it compares. 4 The decision tree for sorting a threeelement list 30 ANALYSIS BASICS leaf represents the worst case. The best case is the shortest path. The average case is the total number of edges in the decision tree divided by the number of leaves in the tree. As simple as it would seem to be able to determine these numbers by drawing decision trees and counting, think about what the decision tree would look like for a sort of 10 numbers.
T ( n ) = 6T ( n ⁄ 6 ) + 2n + 3 T(1) = 1 for n a power of 6 T ( n ) = 4T ( n ⁄ 3 ) + 2n – 1 T(1) = 2 for n a power of 3 3. 4. 7 ANALYZING PROGRAMS Let’s say that we have a large, complex program that takes longer to run than we want. How can we identify parts of this program that with ﬁne-tuning could improve the overall speed? We could look at the program and ﬁnd the subprograms (sometimes called subroutines, procedures, or functions) that have many calculations or loops and work on improving those.