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We will define exponential stability with a weight for generalized nonlinear delay functional differential equations (1).
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This allows us to define exponentials, cosines and logarithms of B directly, for large classes of operators, B; for example, we may define the exponential, e5, of an operator, B, with real spectrum.
That's modeling hockey-stick growth by defining exponential, hockey-stick growth.
These figures show that the KLE decomposition of the uncertain random field is different from the Monte Carlo sampling, in which the heterogeneous profile of random field can be represented by smoother eigenpairs as expressed in Equation (2). Figure 2 (a) Series of λ ¯ n, and (b) its finite cumulative sum for 2D rectangular domain with defined exponential spatial covariance function.
In general, a probability distribution function and expected value of a random variable on a time scale can be defined as follows: By using an exponential function on time scales, we can define an exponential probability density function in a general case and we can define a moment generating function by using Laplace transformations on time scales.
Define the exponential function by (2.4).
Let us define the exponential Jacobi functions by replacing z by (1-2 exp -x/L)).
In this section we shall define the exponential convexity of an operator.
A nonlinear optimization procedure is adopted to fit experimental data and define the exponential Maxwell parameter model.
We define the exponential constraint force at the location of node due to its interaction with node as (12).
Since primitive recursion only allows us to recurse on the first argument, we use two steps to define the exponential function: Finally we can define \(E x,y) = R(\eta y),\eta(x))\) by composition.
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