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MATLAB (an abbreviation of "MATrix LABoratory" [18]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
The sector contour used to calculate the limits of the Fresnel integrals. This can be derived with any one of several methods. One of them [5] uses a contour integral of the function around the boundary of the sector-shaped region in the complex plane formed by the positive x-axis, the bisector of the first quadrant y = x with x ≥ 0, and a circular arc of radius R centered at the origin.
On a semi-log plot the spacing of the scale on the y-axis (or x-axis) is proportional to the logarithm of the number, not the number itself. It is equivalent to converting the y values (or x values) to their log, and plotting the data on linear scales. A log–log plot uses the logarithmic scale for both axes, and hence is not a semi-log plot.
In R software, we compute an empirical cumulative distribution function, with several methods for plotting, printing and computing with such an “ecdf” object. In MATLAB we can use Empirical cumulative distribution function (cdf) plot; jmp from SAS, the CDF plot creates a plot of the empirical cumulative distribution function.
Plot of normalized function (i.e. ()) with its spectral frequency components.. The unitary Fourier transforms of the rectangular function are [2] = = (), using ordinary frequency f, where is the normalized form [10] of the sinc function and = (/) / = (/), using angular frequency , where is the unnormalized form of the sinc function.
A plot of the Q-function. In statistics, the Q-function is the tail distribution function of the standard normal distribution. [1] [2] ... MATLAB and Mathematica.
The above procedure now is reversed to find the form of the function F(x) using its (assumed) known log–log plot. To find the function F, pick some fixed point (x 0, F 0), where F 0 is shorthand for F(x 0), somewhere on the straight line in the above graph, and further some other arbitrary point (x 1, F 1) on the same graph.
Figure (b), right, demonstrates this, showing how initially nearby points begin to diverge, particularly in those regions of x t corresponding to the steeper sections of the plot. Two- and three-dimensional Poincaré plots show the stretching-and-folding structure of the logistic map