The jacobi iterative algorithm has the characteristic of low computational load, and multiple components of the solution can be solved independently. This paper applies these characteristics to the ternary optical com...
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The jacobi iterative algorithm has the characteristic of low computational load, and multiple components of the solution can be solved independently. This paper applies these characteristics to the ternary optical computer, which can be used for parallel optimization because it has a large number of data bits and reconfigurable processor bits. Therefore, a new parallel design scheme is constructed to solve the problem of slow efficiency in solving large linear equations. And the elaborate experiment is used to verify. The experimental method is to simulate the calculation on the ternary optical computer experimental platform. Then, the resource consumption is numerically calculated and summarized to measure the feasibility of the parallel design. Eventually, the results show that the parallel design has obvious advantages in computing speed. The jacobi iterative algorithm is optimized in parallel on ternary optical processor for the first time. There are two parallel highlights of the scheme. First, the n components are calculated in full parallel. Second, the modified signed-digit (MSD) multiplier based on the minimum module and one-step MSD adder are used to calculate each component to eliminate the impact of large amount of data on calculation time. The research provides a new method for fast solution of large linear equations.
Here, the jacobi iterative algorithm is applied to combat intersymbol interference (ISI) caused by frequency-selective channels. The performance bound of the equaliser is analysed in order to gain an insight into its ...
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Here, the jacobi iterative algorithm is applied to combat intersymbol interference (ISI) caused by frequency-selective channels. The performance bound of the equaliser is analysed in order to gain an insight into its asymptotic behaviour. Because of the error propagation problem, the potential of this algorithm is not reached in an uncoded system. However, its extension to a coded system with the application of the turbo-processing principle results in a new turbo equalisation algorithm, which demonstrates comparable performance with reduced complexity compared with some existing filter-based turbo equalisation schemes;and superior performance compared with some frequency domain solutions, such as orthogonal frequency division multiplexing and single-carrier frequency domain equalisation.
Maximisation of the sum-rate of secondary users (SUs), equipped with multi-antenna transmitters and receivers, is considered in the context of multi-input-multi-output antenna multi-band cognitive radio networks (MIMO...
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Maximisation of the sum-rate of secondary users (SUs), equipped with multi-antenna transmitters and receivers, is considered in the context of multi-input-multi-output antenna multi-band cognitive radio networks (MIMO-MB-CRNs) with coexisting primary users (PUs). The total interference power introduced to the PUs is constrained to maintain reliable communication for them. An interference channel configuration is considered for ad hoc networking, where the receivers treat the interference from undesired transmitters as noise. Using game theory approach, the strong duality in convex optimisation and the primal decomposition method, a low complexity semi-distributed algorithm is proposed for spectrum sharing and power allocation for MIMO-MB-CRNs. The key idea behind the algorithm is the introduction of a diagonal block pricing factor matrix for each SU link. This matrix regulates network interference by encouraging SU links to work in a more altruistic manner. The proposed algorithm is configured in two iterativealgorithms, jacobi and Gauss-Seidel algorithms, and their performance is investigated through simulations. The simulation results showed that the proposed algorithm dramatically improves sum-rate and achieves higher energy efficiency, compared with other algorithms.
This paper is dedicated to solving the iterative solution to the discrete-time periodic Sylvester matrix equations. Inspired by jacobi iterative algorithm and hierarchical identification principle, the jacobi gradient...
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This paper is dedicated to solving the iterative solution to the discrete-time periodic Sylvester matrix equations. Inspired by jacobi iterative algorithm and hierarchical identification principle, the jacobi gradient based iterative (JGI) algorithm and the accelerated jacobi gradient based iterative (AJGI) algorithm are proposed. It is verified that the proposed algorithms are convergent for any initial matrix when the parameter factor mu satisfies certain condition. The necessary and sufficient conditions are provided for the presented new algorithms. Moreover, we also apply the JGI algorithm and AJGI algorithm to study a more generalized discrete-time periodic matrix equations and give the convergence conditions of the algorithms. Finally, two numerical examples are given to illustrate the effectiveness, accuracy and superiority of the proposed algorithms. (C) 2021 IMACS. Published by Elsevier B.V. All rights reserved.
Like the Joint Diagonalization of a unique set of matrices, Generalized Joint Diagonalization is an algebraic problem encountered in different applications such as data fusion and blind source separation. This letter ...
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Like the Joint Diagonalization of a unique set of matrices, Generalized Joint Diagonalization is an algebraic problem encountered in different applications such as data fusion and blind source separation. This letter proposes a new generalized unitary joint diagonalization approach based on the jacobiiterative scheme using Givens rotations and simplified criterion, introducing three approximations. These approximations allowed us to reach a simultaneous estimation of different parameters. The first appears in the simplified criterion composed of entries doubly affected by the Givens rotations. The second approximation is in the Givens parameter using a small amplitude angle. The last approximation resides in keeping only the first order of transformed entries. Numerical experiments, including examples of joint blind audio source separation, are provided. The results show the effectiveness of the developed algorithm as compared to existing ones. The simultaneous estimation of different Givens rotations improves the algorithm's computation complexity and convergence rate.
The channel estimation algorithm which has excellent performance is necessary for Single Carrier Frequency Division Multiple Access (SC-FDMA) system. The traditional Least Square (LS) algorithm and Linear Minimum Mean...
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ISBN:
(纸本)9781467372459
The channel estimation algorithm which has excellent performance is necessary for Single Carrier Frequency Division Multiple Access (SC-FDMA) system. The traditional Least Square (LS) algorithm and Linear Minimum Mean-Square (LMMSE) algorithm exist many problems. The problem of the LMMSE algorithm which is too complex is found to be applied effectively by researching LMMSE algorithm. The traditional LMMSE algorithm can be improved with the help of jacobi iterative algorithm for solving linear equations. Meantime, theoretical analysis and simulation results indicate that: The improved LMMSE algorithm has more superior performance at low SNR, it not only can reduce the computational complexity, but also has more precise estimation result.
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