A RADIAL BASIS FUNCTION NETWORK APPROACH FOR THE COMPUTATION OF INVERSE CONTINUOUS TIME VARIANT FUNCTIONS
2007 ◽
Vol 17
(03)
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pp. 149-160
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Keyword(s):
This Paper presents an efficient approach for the fast computation of inverse continuous time variant functions with the proper use of Radial Basis Function Networks (RBFNs). The approach is based on implementing RBFNs for computing inverse continuous time variant functions via an overall damped least squares solution that includes a novel null space vector for singularities prevention. The singularities avoidance null space vector is derived from developing a sufficiency condition for singularities prevention that conduces to establish some characterizing matrices and an associated performance index.
2004 ◽
Vol 13
(03)
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pp. 641-668
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2008 ◽
Vol 19
(3)
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pp. 460-474
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Keyword(s):
2019 ◽
Vol 12
(1)
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pp. 16
2017 ◽
Vol 7
(5)
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pp. 665-669
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Keyword(s):
2018 ◽
Vol 6
(8)
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pp. 827-830