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An early description of a frequency-domain response FDTD method to solve scattering problems was published by Christ and Hartnagel (1987). [3] Another is to find the normal modes of a structure (e.g. a waveguide) in the absence of sources: in this case the frequency ω is itself a variable, and one obtains an eigenproblem A x = λ x ...
The equations and their solutions are applicable from 0 Hz (i.e. direct current) to frequencies at which the transmission line structure can support higher order non-TEM modes. [2]: 282–286 The equations can be expressed in both the time domain and the frequency domain. In the time domain the independent variables are distance and time.
One of the main reasons for using a frequency-domain representation of a problem is to simplify the mathematical analysis. For mathematical systems governed by linear differential equations, a very important class of systems with many real-world applications, converting the description of the system from the time domain to a frequency domain converts the differential equations to algebraic ...
A follow-up paper showed that the classic paired t-test is a central Behrens–Fisher problem with a non-zero population correlation coefficient and derived its corresponding probability density function by solving its associated non-central Behrens–Fisher problem with a nonzero population correlation coefficient. [14]
HOBBIES is a general purpose electromagnetic solver for various applications. [1] The name is an acronym for Higher Order Basis Based Integral Equation Solver.. The software is based on the Method of Moments (MoM), [2] and it employs higher order polynomials as the basis functions for the frequency domain integral equation solver.
The Stanford Research Institute Problem Solver, known by its acronym STRIPS, is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. [1] The same name was later used to refer to the formal language of the inputs to this planner.
A frequency distribution shows a summarized grouping of data divided into mutually exclusive classes and the number of occurrences in a class. It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc.
It has important applications in signal processing, [1] magnetic resonance imaging, [2] and the numerical solution of partial differential equations. [ 3 ] As a generalized approach for nonuniform sampling , the NUDFT allows one to obtain frequency domain information of a finite length signal at any frequency.