In this paper, five novel schemes based on greedy algorithm are proposed to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency division (OFDM) systems. For each proposed scheme, a simple transformat...
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In this paper, five novel schemes based on greedy algorithm are proposed to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency division (OFDM) systems. For each proposed scheme, a simple transformation is performed on the partial transmit sequences in an iterative fashion to lower the PAPR. Computer simulations results show that all the proposed schemes can achieve PAPR reductions, but the performances of the PAPR reduction are different. To further evaluate their PAPR reductions, we compare the proposed schemes with the iterative flipping scheme. The results show that when the number of subblocks is not large, some of the proposed schemes can offer better PAPR reduction performance than the iterative flipping scheme with comparable computational complexity.
In this work we consider the maximum p-facility location problem with k additional resource constraints. We prove that, the simple greedy algorithm has performance guarantee (1 - e(-(k+1)))/(k + 1). In the case k = 0 ...
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In this work we consider the maximum p-facility location problem with k additional resource constraints. We prove that, the simple greedy algorithm has performance guarantee (1 - e(-(k+1)))/(k + 1). In the case k = 0 our performance guarantee coincides with bound due to [4]. (C) 2000 Elsevier Science B.V. All rights reserved.
In this paper, we develop a novel multiway greedy algorithm, named atom-refined multiway orthogonal matching pursuit, for tensor-based compressive sensing (TCS) reconstruction. The alternative supports of each dimensi...
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In this paper, we develop a novel multiway greedy algorithm, named atom-refined multiway orthogonal matching pursuit, for tensor-based compressive sensing (TCS) reconstruction. The alternative supports of each dimension are selected using the respective inner product tensors and refined via a global least square coefficients tensor. For each inner product tensor, the Frobenius-norm (F-norm) of the tensor bands, instead of the largest magnitude entry, is employed to measure the correlation between the atoms and the residual. Theoretical analysis shows that the proposed algorithm could guarantee to exactly reconstruct an arbitrary multi-dimensional block-sparse signal in the absence of noise, provided that the sensing matrices for each dimension satisfy restricted isometry properties with constant parameters. The maximum required number of iterations for exact reconstruction shows an approximate logarithmic growth as the signal size increases. Furthermore, under the noise condition, it is presented that the F-norm of the reconstruction error can be upper-bounded by using the F-norm of noise and the restricted isometry constants of sensing matrices for each dimension. The simulation results demonstrate that the proposed algorithm exhibits obvious advantages as regards both reconstruction accuracy and speed compared with the existing multiway greedy algorithms. Besides TCS, the proposed algorithm also has the potential to be applied in diverse fields, such as hyperspectral image processing and tensor-based dictionary learning.
We prove that the classical bounds on the performance of the greedy algorithm for approximating MINIMUM COVER with costs are valid for PARTIAL COVER as well, thus lowering, by more than a factor of two, the previously...
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We prove that the classical bounds on the performance of the greedy algorithm for approximating MINIMUM COVER with costs are valid for PARTIAL COVER as well, thus lowering, by more than a factor of two, the previously known estimate. In order to do so, we introduce a new simple technique that might be useful for attacking other similar problems. (C) 1997 Published by Elsevier Science B.V.
This study proposed a novel path-planning method for multilink manipulators along the shortest path against obstacles in the plane including three steps. First, the shortest path from the source to the destination is ...
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This study proposed a novel path-planning method for multilink manipulators along the shortest path against obstacles in the plane including three steps. First, the shortest path from the source to the destination is calculated without considering obstacles. Second, whether the optimal path crosses obstacles or not. Finally, a new turning point with shortest path to the collided point and let a new path across this collided point. The shortest path is calculated repeatly until that path does not encounter any obstacle. The proposed greedy algorithm reduces time complexity and information size, and shows good effectiveness for the path planning problem.
In this paper we consider the generalized Walsh system and a problem L-1-convergence of greedy algorithm of functions after changing the values on small set.
In this paper we consider the generalized Walsh system and a problem L-1-convergence of greedy algorithm of functions after changing the values on small set.
Based on the Regularized Functional Matching Pursuit (RFMP) algorithm for linear inverse problems, we present an analogous iterative greedy algorithm for nonlinear inverse problems, called RFMP_NL. In comparison to es...
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Based on the Regularized Functional Matching Pursuit (RFMP) algorithm for linear inverse problems, we present an analogous iterative greedy algorithm for nonlinear inverse problems, called RFMP_NL. In comparison to established methods for nonlinear inverse problems, the algorithm is able to combine very diverse types of basis functions, for example, localized and global functions. This is important, in particular, in geoscientific applications, where global structures have to be distinguished from local anomalies. Furthermore, in contrast to other methods, the algorithm does not require the solution of large linear systems. We apply the RFMP_NL to the nonlinear inverse problem of gravimetry, where gravitational data are inverted for the shape of the surface or inner layer boundaries of planetary bodies. This inverse problem is described by a nonlinear integral operator, for which we additionally provide the Frechet derivative. Finally, we present two synthetic numerical examples to show that it is beneficial to apply the presented method to inverse gravimetric problems.
A weak conical greedy algorithm is introduced with respect to an arbitrary positive complete dictionary in a Hilbert space;this algorithm gives an approximation of an arbitrary space element by a combination of dictio...
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A weak conical greedy algorithm is introduced with respect to an arbitrary positive complete dictionary in a Hilbert space;this algorithm gives an approximation of an arbitrary space element by a combination of dictionary elements with nonnegative coefficients. The convergence of this algorithm is proved and an estimate of the convergence rate for the elements of the convex hull of the dictionary is given.
We show that the convex hull of the set of feasible solutions of single-item capacitated lot-sizing problem (CLSP) is a base polyhedron of a polymatroid. We present a greedy algorithm to solve CLSP with linear objecti...
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We show that the convex hull of the set of feasible solutions of single-item capacitated lot-sizing problem (CLSP) is a base polyhedron of a polymatroid. We present a greedy algorithm to solve CLSP with linear objective function. The proposed algorithm is an effective implementation of the classical Edmonds' algorithm for maximizing linear function over a polymatroid. We consider some special cases of CLSP with nonlinear objective function that can be solved by the proposed greedy algorithm in O(n) time.
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