For a discrete memoryless channel, a lower bound for the correct decoding probability exponent was derived by Arimoto. He also gave an iterative algorithm for computing the exponent. Subsequently, Dueck and Korner det...
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ISBN:
(纸本)9781467377041
For a discrete memoryless channel, a lower bound for the correct decoding probability exponent was derived by Arimoto. He also gave an iterative algorithm for computing the exponent. Subsequently, Dueck and Korner determined the optimal exponent function of the correct decoding probability. In this paper, a new iterative algorithm that computes Dueck and Korner's exponent is presented.
Indoor Visible Light Communication(VLC) positioning is an new indoor positioning method. We discuss the method to realize 3D positioning and the how to optimize it. Build a simplified 3D fingerprint database in the co...
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ISBN:
(纸本)9781628418002
Indoor Visible Light Communication(VLC) positioning is an new indoor positioning method. We discuss the method to realize 3D positioning and the how to optimize it. Build a simplified 3D fingerprint database in the condition of linear light intensity attenuation model and use it for 3D positioning. Furthermore we combined fingerprint database method with the iterative algorithm of Lambert distribution to calculate Z coordinates in order to improve the accuracy. Simulations shows that, in the subspace of 1m*1m*1m, the measurement error of fingerprint database method in X-Y plane is 4.1cm, while z direction measurement error is 5.4cm. By contrast, measurement error of 3D positioning method based on iterative algorithm reduces by 10%.
In this paper, we suggest and analyze an iterative algorithm to approximate a common solution of a hierarchical fixed point problem for nonexpansive mappings, a system of variational inequalities, and a split equilibr...
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In this paper, we suggest and analyze an iterative algorithm to approximate a common solution of a hierarchical fixed point problem for nonexpansive mappings, a system of variational inequalities, and a split equilibrium problem in Hilbert spaces. Under some suitable conditions imposed on the sequences of parameters, we prove that the sequence generated by the proposed iterative method converges strongly to a common element of the solution set of these three kinds of problems. The results obtained here extend and improve the corresponding results of the relevant literature.
The purpose of this paper is to introduce new iterative algorithms for approximating a solution to a class of monotone operator equations. More precisely, we study the split common solution problem with multiple outpu...
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The purpose of this paper is to introduce new iterative algorithms for approximating a solution to a class of monotone operator equations. More precisely, we study the split common solution problem with multiple output sets for monotone operator equations in Hilbert spaces. In order to solve this problem, we propose three new algorithms and establish strong convergence theorems for them.
In this paper, we propose a new iterative algorithm and analyze it in detail inasmuch as convergence, stability, and data dependency for the class of almost contraction mappings. We also consider another iterative alg...
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In this paper, we propose a new iterative algorithm and analyze it in detail inasmuch as convergence, stability, and data dependency for the class of almost contraction mappings. We also consider another iterative algorithm called F* iterative algorithm proposed by Ali et al. (Comp. Appl. Math. 39, 267 (2020)) and derive some new algorithms from this with the aim of giving an affirmative answer to an open question raised by the same authors. Our results considerably improve the corresponding results in Ali et al. (Comp. Appl. Math. 39, 267 (2020)). We submit some non-trivial numerical examples to illustrate the robustness, feasibility, and effectiveness of our findings.
The influence of inaccurate knowledge still exists in the Semantic Web. The problem of knowledge inaccuracy in Knowledge Bases (KBs) is one of the largest obstacles that limit the development of Linked Open Data (LOD)...
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The influence of inaccurate knowledge still exists in the Semantic Web. The problem of knowledge inaccuracy in Knowledge Bases (KBs) is one of the largest obstacles that limit the development of Linked Open Data (LOD) and Knowledge Graphs (KGs). To solve the semantic ambiguity and improper classification of knowledge triples in the process of constructing Chinese online encyclopedia KBs, first, a new TF-AICL algorithm is proposed to calculate the concentration level of predicates in each top-category. Second, the predicate which can best represent the features of a top-category is selected, and the related predicate candidate set is extracted. Third, based on the positive and negative examples counting strategy, the predicate candidate set is used as the comparison group to filter each entity. Finally, based on the TF-AICL algorithm, this paper proposes a new iterative filtering method called IFTA. IFTA adopts a new predicate feature extraction method, TF-AICL, which considers the hierarchical features of the predicate. In addition, IFTA can automatically prune, filter and refine large-scale online encyclopedia knowledge in an iterative way. The precision, recall and F-measure results on the BaiduBaike and Hudong datasets indicate that the refining effects on open-domain Chinese encyclopedia KBs by the IFTA method outperform the state-of-the-art methods.
With the large-scale integration of renewable energy,the traditional maintenance arrangement during the load valley period cannot satisfy the transmission demand of renewable energy ***,in a market-oriented operation ...
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With the large-scale integration of renewable energy,the traditional maintenance arrangement during the load valley period cannot satisfy the transmission demand of renewable energy ***,in a market-oriented operation mode,the power dispatching control center aims to reduce the overall power purchase cost while ensuring the security of the power ***,a security-constrained transmission maintenance optimization model considering generation and operational risk costs is proposed *** model is built on double-layer optimization framework,where the upper-layer model is used for maintenance and generation planning,and the lowerlayer model is primarily used to address the operational security risk arising from the random prediction error and N-1 transmission ***,a generation-maintenance iterative algorithm based on a defined cost feedback is included to increase solution *** cost is determined using long-term security-constrained unit commitment,and the operational risk cost is obtained using a double-layer N-1 risk assessment *** electrical correlation coupling coefficient is proposed for the solution process to avoid maintenance of associated equipment simultaneously,thereby improving model convergence *** IEEE 118-bus system is used as a test case for illustration,and test results suggest that the proposed model and algorithm can reduce the total cost of transmission maintenance and system operation while effectively improving the solution efficiency of the joint optimization model.
Due to the 'soft-field' effect and the challenges posed by ill-posed and ill-conditioned inverse problems, it is difficult to obtain high quality images from an electrical capacitance tomography (ECT) system. ...
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Due to the 'soft-field' effect and the challenges posed by ill-posed and ill-conditioned inverse problems, it is difficult to obtain high quality images from an electrical capacitance tomography (ECT) system. To achieve both high-quality images and fast imaging speed with limited measurement data, an image reconstruction algorithm, which was initially proposed for compressive sensing, is adapted for ECT image reconstruction to optimize the ill-posed nature of its inverse problem. The proposed algorithm leverages deep learning networks inspired by the iterative shrinkage-thresholding algorithm (ISTA), thereby creating a model that is both mathematically interpretable and endowed with trainable parameters. Building upon this foundation, the conventional Landweber iteration is integrated with the ISTA-Net to refine the optimization process for ECT image reconstruction. In order to propose an effective model adapting to the actual multiphase flow characteristics and complex flow pattern changes, the training and test process is driven by a comprehensive dataset generated from dynamic simulations, rather than artificial samples of multiphase distributions. This numerical methodology simulates the dynamic measurement process of a virtual ECT sensor by coupling the gas-liquid two-phase flow field and the ECT electrostatic field. The results of the testing phase indicate that the proposed algorithm outperforms traditional ECT image reconstruction methods. Compared with the linear back projection algorithm, the average image error and gas fraction error have been reduced by 20.44% and 16.74%, respectively, while maintaining a computational speed comparable to that of the Landweber iteration. The accuracy of the new algorithm in reconstructing the two-phase interface and estimating the gas fraction has been validated by static experimental tests, showing its potential for practical application in online gas-liquid two-phase flow measurement scenarios.
In this paper, we design an iterative channel estimation and data detection algorithm in delay-Doppler domain for orthogonal time frequency space (OTFS) system by taking advantage of the sparse nature of the channel i...
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ISBN:
(纸本)9781665405409
In this paper, we design an iterative channel estimation and data detection algorithm in delay-Doppler domain for orthogonal time frequency space (OTFS) system by taking advantage of the sparse nature of the channel in this domain. The proposed algorithm iterates between message-passing-aided data detection and data-aided channel estimation. This sparse channel estimation is reformulated as a specific marginalization of maximum a posteriori (MAP) problem. To deal with the intractability of this problem, we provide a Bayesian approach based on the variational mean-field approximation via the variational Bayesian expectation maximization (VB-EM) algorithm. Finally, we compare the complexity and performance in term of Bit Error Rate (BER) and Normalized Mean Square Error (NMSE) of the proposed solution to a reference solution in the literature (SP-I).
This paper is concerned with iterative solution to general Sylvester-conjugate matrix equation of the form Sigma(i) (=) (s)(1) A(i) V + Sigma(t)(j = 1) B-j W = Sigma(m)(l = 1) E-l (V) over bar F-l + C. An iterative al...
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This paper is concerned with iterative solution to general Sylvester-conjugate matrix equation of the form Sigma(i) (=) (s)(1) A(i) V + Sigma(t)(j = 1) B-j W = Sigma(m)(l = 1) E-l (V) over bar F-l + C. An iterative algorithm is established to solve this matrix equation. When this matrix equation is consistent, for any initial matrices, the solutions can be obtained within finite iterative steps in the absence of round off errors. Some lemmas and theorems are stated and proved where the iterative solutions are obtained. Finally, a numerical example is given to verify the effectiveness of the proposed algorithm.
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