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When dealing with musical instrument sounds, ideally, each basis function can represent a single pitch, and the corresponding gains contain information about the onset and offset times of notes having that pitch.
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Also, a Gaussian basis function can be used to sparsely represent environmental signals [37].
Then the network basis function can be formed.
Then, the other basis functions can be obtained by samples cycle shifting operation on, where l represents the shifting factor.
Generating functions for the Bernstein basis functions can be defined as follows.
First, since linear Lagrange basis functions can only represent a linear continuous function, the fundamental limitation of this approach is that discontinuity in an optical parameter distribution cannot be represented.
The main idea behind the estimation paradigm proposed herein is that the DW set of functions is a sparsifying basis for the cost-to-go function c ¯. Due to the structured behavior defined by networking protocols, a small number of functions can represent the evolution and, thus, the collected cost, from large groups of states.
Several basis functions can jointly mask one or several other basis functions.
Note that the number of basis functions can differ between random effects.
After decompositions, we can use the cost function-searching algorithm to find the best basis set ( left{{D}_l^{ k)}right} ) among all the possible basis sets, which can represent the spatial and frequency domain information of the analyzed dataset more effectively than all other basis sets.
(2) The radial basis function kernel can better represent the nonlinearity appearing in HRRP samples than the polynomial function kernel.
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