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For example, the derivative of the sine function is written sin ′ (a) = cos(a), meaning that the rate of change of sin(x) at a particular angle x = a is given by the cosine of that angle. All derivatives of circular trigonometric functions can be found from those of sin(x) and cos(x) by means of the quotient rule applied to functions such as ...
Then multiplying the numerator and denominator inside the square root by (1 + cos θ) and using Pythagorean identities leads to: = + . Also, if the numerator and denominator are both multiplied by (1 - cos θ), the result is:
A calculation confirms that z(0) = 1, and z is a constant so z = 1 for all x, so the Pythagorean identity is established. A similar proof can be completed using power series as above to establish that the sine has as its derivative the cosine, and the cosine has as its derivative the negative sine.
Consider the problem of finding the positive number x with cos x = x 3. We can rephrase that as finding the zero of f(x) = cos(x) − x 3. We have f ′ (x) = −sin(x) − 3x 2. Since cos(x) ≤ 1 for all x and x 3 > 1 for x > 1, we know that our solution lies between 0 and 1.
Ptolemy's theorem states that the sum of the products of the lengths of opposite sides is equal to the product of the lengths of the diagonals. When those side-lengths are expressed in terms of the sin and cos values shown in the figure above, this yields the angle sum trigonometric identity for sine: sin(α + β) = sin α cos β + cos α sin β.
In his article, [1] Milne-Thomson considers the problem of finding () when 1. u ( x , y ) {\displaystyle u(x,y)} and v ( x , y ) {\displaystyle v(x,y)} are given, 2. u ( x , y ) {\displaystyle u(x,y)} is given and f ( z ) {\displaystyle f(z)} is real on the real axis, 3. only u ( x , y ) {\displaystyle u(x,y)} is given, 4. only v ( x , y ...
In Cartesian coordinates, the divergence of a continuously differentiable vector field = + + is the scalar-valued function: = = (, , ) (, , ) = + +.. As the name implies, the divergence is a (local) measure of the degree to which vectors in the field diverge.
[a] This means that the function that maps y to f(x) + J(x) ⋅ (y – x) is the best linear approximation of f(y) for all points y close to x. The linear map h → J(x) ⋅ h is known as the derivative or the differential of f at x. When m = n, the Jacobian matrix is square, so its determinant is a well-defined function of x, known as the ...