TAILIEUCHUNG - Engineering Matlab Problem Solving phần 10

then g(x) is the derivative of f (x) with respect to x. This relationship is written as g(x) = df (x) = f (x) dx The derivative f (x) can be interpreted geometrically as the slope of the function at (x, f (x)), where the slope of f (x) is the slope of the tangent line to the function at x, as shown in Figure . Figure : Derivative of f (x) at x = a. Formally, the derivative of f at x is f (x) = lim f (x + ∆x) − f (x) f (x + ∆x) − f (x). | then g x is the derivative of f x with respect to x. This relationship is written as g x f f x The derivative f x can be int S rrt ed g t n -tiik Ễìiy as the sO s e of the functton at x f x where the slope of f x ĨS the stope of the t jgg j t ime to the funciton at x as shown in Figure . Figure Derivative of f x at x a. Formally the derivative of f at x is f x im f x Ax f x f x A 0 x Ax - x f x Ax - f x A 0 Ax Difference Expressions Numerical differentiation techniques estimate the derivative of a function at a point xk by approximating the slope of the tangent line at xk using values of the function at points near xk. The approximation of the slope of the tangent line can be done in several ways as shown in Figure . The backward difference approximation of the derivative at xk is the slope of the line between f xk-1 and f xk as shown in Figure f xk f xk - f xk-1 xk xk-1 If the samples of x are uniformly spaced so that xk xk-1 Ax f xk fx f xk-l k Ax The forward difference approximation of the derivative at xk is the slope of the line between f xk and f xk 1 as shown in Figure f xk f xk 1 f xk xk i xk 231 For uniform spacing Ax f xk ÍÍXíilị-ÍÍXd Ax Note that the forward difference at xk is the same as the backward difference at xk 1. Figure Techniques for approximating f xk . The quality of both of these derivative approximations depends heavily on two factors the spacing of the samples and the scatter in the data due to measurement error. The greater the spacing the more difficult it is to estimate the derivative. The approximation improves as the spacing between the two points decreases. The central difference is the average of the forward and backward differences. For uniform spacing f xfc 1 Ợ xk 1 - f xk f xk - f xk-1 f xk 1 - f xk-1 Ax This average tends to cancel out the effects of measurement error. The second derivative of a function f x is the derivative of the firtt derivative of the function f xk df x dx This function can be

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