7,634 research outputs found
Idempotent permutations
Together with a characteristic function, idempotent permutations uniquely
determine idempotent maps, as well as their linearly ordered arrangement
simultaneously. Furthermore, in-place linear time transformations are possible
between them. Hence, they may be important for succinct data structures,
information storing, sorting and searching.
In this study, their combinatorial interpretation is given and their
application on sorting is examined. Given an array of n integer keys each in
[1,n], if it is allowed to modify the keys in the range [-n,n], idempotent
permutations make it possible to obtain linearly ordered arrangement of the
keys in O(n) time using only 4log(n) bits, setting the theoretical lower bound
of time and space complexity of sorting. If it is not allowed to modify the
keys out of the range [1,n], then n+4log(n) bits are required where n of them
is used to tag some of the keys.Comment: 32 page
Battery Charge Applications Based on Wide Output Voltage Range
In this study, high efficiency design procedure of a phase shifted full bridge (PSFB) converter is presented for on-board electrical vehicle (EV) battery charger. Presented design methodology used lithium-ion battery cells because of their high voltage and current rates compared to a lead-acid battery cells. In this case, PSFB converter can be regulated wide range output voltage with while its soft switching operation is maintained. The basic operation principles of PSFB converter is defined and its soft switching operation requirements are given. To evaluate the performance of the converter over wide output voltage range, zero voltage switching (ZVS) operation of converter is discussed based on dead time requirement. To improve efficiency, the snubber inductance effects on soft switching over wide output voltage range are evaluated. Finally, operation of the PSFB converter is validated experimentally with a prototype which has 42-54 V/15 A output range at 200 kHz switching frequency
Denosing Using Wavelets and Projections onto the L1-Ball
Both wavelet denoising and denosing methods using the concept of sparsity are
based on soft-thresholding. In sparsity based denoising methods, it is assumed
that the original signal is sparse in some transform domains such as the
wavelet domain and the wavelet subsignals of the noisy signal are projected
onto L1-balls to reduce noise. In this lecture note, it is shown that the size
of the L1-ball or equivalently the soft threshold value can be determined using
linear algebra. The key step is an orthogonal projection onto the epigraph set
of the L1-norm cost function.Comment: Submitted to Signal Processing Magazin
Phase and TV Based Convex Sets for Blind Deconvolution of Microscopic Images
In this article, two closed and convex sets for blind deconvolution problem
are proposed. Most blurring functions in microscopy are symmetric with respect
to the origin. Therefore, they do not modify the phase of the Fourier transform
(FT) of the original image. As a result blurred image and the original image
have the same FT phase. Therefore, the set of images with a prescribed FT phase
can be used as a constraint set in blind deconvolution problems. Another convex
set that can be used during the image reconstruction process is the epigraph
set of Total Variation (TV) function. This set does not need a prescribed upper
bound on the total variation of the image. The upper bound is automatically
adjusted according to the current image of the restoration process. Both of
these two closed and convex sets can be used as a part of any blind
deconvolution algorithm. Simulation examples are presented.Comment: Submitted to IEEE Selected Topics in Signal Processin
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