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We consider superlinearly convergent analogues of Newton methods for nondiier-entiable operator equations in function spaces. The superlinear convergence analysis of semismooth methods for nondiierentiable equations described by deening a locally Lipschitzian operator in R n is based on Rademacher's theorem which does not hold in function spaces. We(More)
We present a local convergence analysis of generalized Newton methods for singular smooth and nonsmooth operator equations using adaptive constructs of outer inverses. We prove that for a solution x of F(x) = 0, there exists a ball S = S(x ; r), r > 0 such that for any starting point x 0 2 S the method converges to a solution x 2 S of ?F (x) = 0, where ? is(More)
Characterization of quasiconvexity and pseudoconvexity of lower semicontinuous functions on Banach spaces are presented in terms of abstract subdifferentials relying on a Mean Value Theorem. We give some properties of the normal cone to the lower level set of f. We also obtain necessary and sufficient optimality conditions in quasiconvex and pseudoconvex(More)
In automatic target recognition (ATR), correlation filters are widely used to detect target signature variations. In this paper we concentrate on a particular case: target pose angle. For the traditional maximum average correlation height (MACH) filter method, only a few special angles can be used due to the limitation of the training data and the(More)
We consider reconstruction of signals by a direct method for the solution of the discrete Fourier system. We note that the reconstruction of a time-limited signal can be simply realized by using only either the real part or the imaginary part of the discrete Fourier transform (DFT) matrix. Therefore, based on the study of the special structure of the real(More)
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