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e aX e bX = e (a + b)X; e X e −X = I; Using the above results, we can easily verify the following claims. If X is symmetric then e X is also symmetric, and if X is skew-symmetric then e X is orthogonal. If X is Hermitian then e X is also Hermitian, and if X is skew-Hermitian then e X is unitary.
The study of these differential equations with constant coefficients dates back to Leonhard Euler, who introduced the exponential function e x, which is the unique solution of the equation f′ = f such that f(0) = 1. It follows that the n th derivative of e cx is c n e cx, and this allows solving homogeneous linear differential equations ...
For instance, e x can be defined as (+). Or e x can be defined as f x (1), where f x : R → B is the solution to the differential equation df x / dt (t) = x f x (t), with initial condition f x (0) = 1; it follows that f x (t) = e tx for every t in R.
The last expression is the logarithmic mean. = ( >) = (>) (the Gaussian integral) = (>) = (, >) (+) = (>)(+ +) = (>)= (>) (see Integral of a Gaussian function
In all these cases, y is an unknown function of x (or of x 1 and x 2), and f is a given function. He solves these examples and others using infinite series and discusses the non-uniqueness of solutions. Jacob Bernoulli proposed the Bernoulli differential equation in 1695. [3] This is an ordinary differential equation of the form
Define () = to be the unique solution to the differential equation with initial value: ′ =, =, where ′ = denotes the derivative of y. Functional equation. The exponential function e x {\displaystyle e^{x}} is the unique function f with the multiplicative property f ( x + y ) = f ( x ) f ( y ) {\displaystyle f(x+y)=f(x)f(y)} for all x , y ...
with the derivative evaluated at = Another connexion with the confluent hypergeometric functions is that E 1 is an exponential times the function U(1,1,z): = (,,) The exponential integral is closely related to the logarithmic integral function li(x) by the formula
When x and y are real variables, the derivative of f at x is the slope of the tangent line to the graph of f at x. Because the source and target of f are one-dimensional, the derivative of f is a real number. If x and y are vectors, then the best linear approximation to the graph of f depends on how f changes in several directions at once.
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