Examples of 'basis functions' in a sentence

Meaning of "basis functions"

Refers to the fundamental or essential functions upon which a system, process, or theory is built. These functions serve as the core components or building blocks of a larger structure or concept

How to use "basis functions" in a sentence

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basis functions
Basis functions are linear or higher order polynomials.
Solving PDEs with radial basis functions.
The set of basis functions is usually called a dictionary.
We will start with quadratic basis functions.
Basis functions that have this property are called orthognal.
Linear combinations of these basis functions.
These basis functions are short waves with limited duration.
Abinitio calculations using various types of basis functions.
Sums of radial basis functions are typically used to approximate given functions.
As a linear combination of these basis functions.
In this case the basis functions are equal to the feature values.
The motion model generally comprises a set of basis functions.
These basis functions can model interaction between two or more variables.
Zernike polynomials are widely used as basis functions of image moments.
The basis functions of the wavelet transform are scaled with respect to frequency.

See also

This is not the case for other radial basis functions.
Usually these basis functions oscillate rapidly and are identified with noise.
Any continuous function can be represented as a linear combination of basis functions.
This is affected by choosing suitable basis functions that allow for this.
The thin plate spline has a natural representation in terms of radial basis functions.
It is discretized with basis functions conform to the mapping properties of the involved operators.
Spin orbitals can be expressed as the linear combination of basis functions.
We implemented radial basis functions to approximate the constraint and the objective functions.
There are many different wavelets that can be used as basis functions.
These families of basis functions offer a more parsimonious fit for many types of data.
In general the clutter or plot density can be expanded on a set of basis functions.
The spatial basis functions depend on the sound directions but are independent on the frequency.
The output of the network is a linear combination of the outputs from radial basis functions.
Investigation of orthogonal basis functions for adaptive Wiener models.
The model includes further innovations like the use of piecewise sinusoidal basis functions.
The Gaussian basis functions are local to the center vector in the sense that.
Some integer transforms have the property that different basis functions have different norms.
Radial basis functions were first introduced by Powell to solve the real multivariate interpolation problem.
The resulting motion vector field is represented using certain basis functions and motion coefficients.
Basis functions in DCT.
There exist different but closely related mathematical definitions for the different spatial basis functions.
Kernel distance functions and radial basis functions Singular Boundary Method.
The Fourier series is a method of expressing a periodic function in terms of sinusoidal basis functions.
Then, the one or more spatial basis functions needed are determined.
So, just as we did before we will construct basis functions.
One usually makes use of basis functions which are local, repetitive and separable.
Therefore, we represent data by means of basis functions.
In particular, for basis functions that are only supported locally, the stiffness matrix is sparse.
Then, the required one or more spatial basis functions are determined.
Alternatively, various basis functions such as a spline function and a polynomial function may be used.
Knowing the percentage of unexplained variance when using x basis functions e . g.
Using the low degree Raviart-Thomas basis functions allows to get the piecewise constant reconstruction property.
In this example, the sines and cosines are the basis functions.
The basis functions chosen are local, separable, repetitive and Gaussian basis functions.
The overlap matrix is always n × n, where n is the number of basis functions used.

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