Search results
Results From The WOW.Com Content Network
The matrix exponential satisfies the following properties. [2] We begin with the properties that are immediate consequences of the definition as a power series: e 0 = I; exp(X T) = (exp X) T, where X T denotes the transpose of X. exp(X ∗) = (exp X) ∗, where X ∗ denotes the conjugate transpose of X. If Y is invertible then e YXY −1 = Ye ...
Given that (which can be computed using any suitable tool, such as MATLAB's expm tool, or by performing matrix diagonalisation and leveraging the property that the matrix exponential of a diagonal matrix is the same as element-wise exponentiation of its elements)
Expm or expm may refer to: expm1, an abbreviation for the exponent minus 1 function in some Hewlett-Packard RPL scientific calculators; Matrix exponential, the generalization of the exponential function to matrices.
In cases where (), are expressed by polynomials or series of negative powers, exponential function, logarithmic function or , we can apply 2-point Padé approximant to (). There is a method of using this to give an approximate solution of a differential equation with high accuracy. [ 9 ]
The number e is a mathematical constant approximately equal to 2.71828 that is the base of the natural logarithm and exponential function.It is sometimes called Euler's number, after the Swiss mathematician Leonhard Euler, though this can invite confusion with Euler numbers, or with Euler's constant, a different constant typically denoted .
The exponential of a variable is denoted or , with the two notations used interchangeably. It is called exponential because its argument can be seen as an exponent to which a constant number e ≈ 2.718, the base, is raised. There are several other definitions of the exponential function, which are all equivalent ...
Taylor Swift shared on her Instagram story that she has donated to 10 organizations in the Los Angeles area, which is experiencing widespread wildfire devastation. "The fires in California have ...
In probability theory, an exponentially modified Gaussian distribution (EMG, also known as exGaussian distribution) describes the sum of independent normal and exponential random variables. An exGaussian random variable Z may be expressed as Z = X + Y, where X and Y are independent, X is Gaussian with mean μ and variance σ 2, and Y is ...