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Academic literature on the topic 'Forward-And-Backward algorithm'

Author: Grafiati

Published: 25 May 2024

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Journal articles on the topic "Forward-And-Backward algorithm"

1

Wang, Feng, Jianping Zhang, Guiling Sun, and Tianyu Geng. "Iterative Forward-Backward Pursuit Algorithm for Compressed Sensing." Journal of Electrical and Computer Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/5940371.

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It has been shown that iterative reweighted strategies will often improve the performance of many sparse reconstruction algorithms. Iterative Framework for Sparse Reconstruction Algorithms (IFSRA) is a recently proposed method which iteratively enhances the performance of any given arbitrary sparse reconstruction algorithm. However, IFSRA assumes that the sparsity level is known. Forward-Backward Pursuit (FBP) algorithm is an iterative approach where each iteration consists of consecutive forward and backward stages. Based on the IFSRA, this paper proposes the Iterative Forward-Backward Pursui

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2

Renugadevi, S., Aayush S. Rawat, Suraj Swaminathan, P. Arulmozhivarman, and R. Selvakumar. "Perimeter coverage using backward and forward greedy algorithm." Applied Mathematical Sciences 7 (2013): 3883–96. http://dx.doi.org/10.12988/ams.2013.34203.

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3

Moursi, Walaa M. "The Forward–Backward Algorithm and the Normal Problem." Journal of Optimization Theory and Applications 176, no. 3 (2018): 605–24. http://dx.doi.org/10.1007/s10957-017-1113-4.

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4

Chen, Jinjian, Xingyu Luo, Yuchao Tang, and Qiaoli Dong. "Primal-Dual Splitting Algorithms for Solving Structured Monotone Inclusion with Applications." Symmetry 13, no. 12 (2021): 2415. http://dx.doi.org/10.3390/sym13122415.

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This work proposes two different primal-dual splitting algorithms for solving structured monotone inclusion containing a cocoercive operator and the parallel-sum of maximally monotone operators. In particular, the parallel-sum is symmetry. The proposed primal-dual splitting algorithms are derived from two approaches: One is the preconditioned forward–backward splitting algorithm, and the other is the forward–backward–half-forward splitting algorithm. Both algorithms have a simple calculation framework. In particular, the single-valued operators are processed via explicit steps, while the set-v

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5

Tottori, Takehiro, and Tetsuya J. Kobayashi. "Forward and Backward Bellman Equations Improve the Efficiency of the EM Algorithm for DEC-POMDP." Entropy 23, no. 5 (2021): 551. http://dx.doi.org/10.3390/e23050551.

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Decentralized partially observable Markov decision process (DEC-POMDP) models sequential decision making problems by a team of agents. Since the planning of DEC-POMDP can be interpreted as the maximum likelihood estimation for the latent variable model, DEC-POMDP can be solved by the EM algorithm. However, in EM for DEC-POMDP, the forward–backward algorithm needs to be calculated up to the infinite horizon, which impairs the computational efficiency. In this paper, we propose the Bellman EM algorithm (BEM) and the modified Bellman EM algorithm (MBEM) by introducing the forward and backward Bel

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Jannati, Mohammad, Tole Sutikno, Nik Rumzi Nik Idris, and Mohd Junaidi Abdul Aziz. "High Performance Speed Control of Single-Phase Induction Motors Using Switching Forward and Backward EKF Strategy." International Journal of Power Electronics and Drive Systems (IJPEDS) 7, no. 1 (2016): 17. http://dx.doi.org/10.11591/ijpeds.v7.i1.pp17-27.

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<p>The aim of this research is to provide a high performance vector control of single-phase Induction Motor (IM) drives. It is shown that in the rotating reference frame, the single-phase IM equations can be separated into forward and backward equations with the balanced structure. Based on this, a method for vector control of the single-phase IM, using two modified Rotor Field-Oriented Control (RFOC) algorithms is presented. In order to accommodate forward and backward rotor fluxes in the presented controller, an Extended Kalman Filter (EKF) with two different forward and backward curre

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7

Liu, Liya, Xiaolong Qin, and Jen-Chih Yao. "A Hybrid Forward–Backward Algorithm and Its Optimization Application." Mathematics 8, no. 3 (2020): 447. http://dx.doi.org/10.3390/math8030447.

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In this paper, we study a hybrid forward–backward algorithm for sparse reconstruction. Our algorithm involves descent, splitting and inertial ideas. Under suitable conditions on the algorithm parameters, we establish a strong convergence solution theorem in the framework of Hilbert spaces. Numerical experiments are also provided to illustrate the application in the field of signal processing.

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8

Stankovic, Marko, Miroslav Ciric, and Jelena Ignjatovic. "Simulations and bisimulations for fuzzy multimodal logics over Heyting algebras." Filomat 37, no. 3 (2023): 711–43. http://dx.doi.org/10.2298/fil2303711s.

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In the present paper, we study fuzzy multimodal logics over complete Heyting algebras and Kripke models for these logics. We introduce two types of simulations (forward and backward) and five types of bisimulations (forward, backward, forward-backward, backward-forward and regular) between Kripke models, as well as the corresponding presimulations and prebisimulations, which are simulations and bisimulations with relaxed conditions. For each type of simulations and bisimulations an efficient algorithm has been provided that works as follows: it computes the greatest presimulation/prebisimulati

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9

Bussaban, Limpapat, Attapol Kaewkhao, and Suthep Suantai. "Inertial s-iteration forward-backward algorithm for a family of nonexpansive operators with applications to image restoration problems." Filomat 35, no. 3 (2021): 771–82. http://dx.doi.org/10.2298/fil2103771b.

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Image restoration is an important branch of image processing which has been studied extensively while there are several methods to solve this problem by many authors with the challenges of computational speed and accuracy of algorithms. In this paper, we present two methods, called ?Inertial S-iteration forward-backward algorithm (ISFBA)? and ?A fast iterative shrinkage-thresholding algorithm-Siteration (FISTA-S)?, for finding an approximate solution of least absolute shrinkage and selection operator problem by using a special technique in fixed point theory and prove weak convergence of the p

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10

MUNEHISA, TOMO, and HIDEKAZU TANAKA. "ALGORITHM DEPENDENCE OF PARTON SHOWERS IN DEEP INELASTIC SCATTERING." International Journal of Modern Physics A 06, no. 06 (1991): 989–1002. http://dx.doi.org/10.1142/s0217751x9100054x.

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Parton showers for deep inelastic electron-proton scattering are studied. Forward and backward evolution algorithms are constructed using the same definitions for splitting and evolution variables. We discuss features of two algorithms and examine algorithm dependence of final parton distributions.

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