Pricing American Options by a Fourier Transform Multinomial Tree in a Conic Market by Weiwei Wang, Xiaoping Hu

“…Then, the American option pricing method based on reverse iteration is given. Finally, the CGMY process is used to demonstrate how to price the American put option in the Lévy conic market. …”
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On the Solutions of Nonlinear Algebraic and Transcendental Equations using Adomian Decomposition Method by Gbeminiyi Musibau Sobamowo, Antonio Marcos de Oliveira Siqueira

“…Also, the method as applied in this study shows that it does not require the development of any other iterative scheme that could be used to find the solution to the nonlinear equations. …”
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A non-linear model of information seeking behaviour by Allen E. Foster

“…Coding of interview transcripts took place in multiple iterations over time and used Atlas-ti software to support the process. …”
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CSI feedback algorithm based on deep unfolding for massive MIMO systems by Yong LIAO, Gang CHENG, Yujie LI

“…In order to solve the problem that the channel state information (CSI) feedback algorithm based on deep learning in massive MIMO systems at present had too many parameters to be trained and could not be explained well, two CSI feedback algorithms based on depth expansion were proposed.The first one was approximate message delivery (AMP) algorithm based on learnable parameters.The learnable parameters in deep learning were used to replace the threshold value of the threshold function in the AMP algorithm and the parameters of the Onsage correction term.The nonlinear ability of threshold function in dealing with non-strict sparse data was enhanced.The other was the AMP algorithm based on convolutional network, which replaced the threshold function module with the convolutional residual learning module, and used the module to remove the Gaussian random noise generated by each iteration of the AMP algorithm.Simulation results show that the proposed two algorithms have better CSI feedback performance than AMP algorithm, and the AMP algorithm based on convolutional network has better CSI reconstruction performance than the representative method based on deep learning.…”
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Novel Feature Selection Method for Nonlinear Support Vector Regression by Kejia Xu, Ying Xu, Yafen Ye, Weijie Chen

“…FS-NSVR is a challenging mixed-integer programming problem that is solved efficiently by using an alternate iterative greedy algorithm. Experimental results on three artificial datasets and five real-world datasets confirm that FS-NSVR effectively selects representative features and discards redundant features in a nonlinear system. …”
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Simulation System of Space-Air-Ground Integrated Micro-Service New Network Architecture in 6G by Junyi YANG, Fandi PEI, Zhaolong XU, Zhenyu XIAO

“…The space-air-ground integrated network is the inevitable trend of 6G development in the future.A set of verifi cation simulation system was designed and set up for the micro-service new network architecture of space-air-ground integrated network in 6G.A four-layer simulation system architecture was proposed, included access user layer, radio unit-distributed unit (RU-DU) layer, NFV case management layer and micro-service network element layer.The whole process of network topology establishment, user registration, session establishment and communication case simulation could be realized, which embodied the function of service-oriented network element.Three basic simulation communication cases, namely communication between users, handover management and session management, were designed, and the feasibility of the new network architecture was verifi ed by the handover management case, which laid the engineering foundation for the iterative evolution of network architecture.…”
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Cognitive Waveform Design for Radar-Communication Transceiver Networks by Yu Yao, Lenan Wu

“…In addition to theoretical considerations, the simulation results show an improvement in target scattering coefficient (TSC) estimation and target detection probability as the number of iterations increases, while still transmitting data rates in the range of several Mbps with low bit error rates between CRC transceivers.…”
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Secure communication approach for Internet of things based on C-RAN fronthaul compression by Yong WANG, Mu ZHOU, Zengshan TIAN, Jinjun WU

“…A resource allocation algorithm was proposed for downlink C-RAN secure communication system.This algorithm jointly optimized the parameters of base station (BS) mode,quantized noise and beamforming under the constraints of SINR requirements of Internet of things information receiver,eavesdropped receiver and fronthaul link capacity.Such a design was a non-convex optimization problem,and a step-by step optimization algorithm was proposed to decompose the original optimization problem efficiently.Semi-definite technique and function smoothing approach were adopted,and the local optimization solution of the original problem was obtained by the iterative different of convex method.Bi-section approach was further proposed to determine BS mode,and the transmitting power of the BSs were finally optimized.Simulation results indicate that the proposed joint optimization algorithm achieves better performance than group sparse optimization algorithm and baseline algorithm,and it has approximate optimal performance as the exhaustive search algorithm.…”
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Analysis of the Positional Forward Solution of 2（3-RPS） Parallel-serial Robot Motion Mechanism by 李峰, 李伟, 梁辉

“…Firstly,the position coordinates of spherical joints on the upper platform of 3-RPS parallel mechanism are derived based on its structural characteristics,and then,a set of equations are listed according to the fixed side value of motion platform of each parallel mechanism,using iterative transformation method,a 16 order equation with one unknown variable is gained. …”
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A Novel Massive Big Data Analysis of Educational Examination Research Using a Linear Mixed-Effects Model by Jing Zhao, Yiwen Wang

“…First, a three-step estimation method is proposed to improve the parameters of the linear-effects model, avoiding the complicated iterative steps of maximum likelihood estimation. Second, we perform spectral clustering based on test data on the basis of defining data attributes and basic evaluation rules. …”
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FAULT FEATURE EXTRACTION OF ROLLING ELEMENT BEARINGS BASED ON ADAPTIVE MCKD by CHEN BingYan, SONG DongLi, ZHANG WeiHua, CHENG Yao, LI JiaYuan

“…Considering the shortcomings of the maximum correlated kurtosis deconvolution（MCKD） method that cannot automatically identify the period of bearing fault impulses,exists the resampling process and the multiple input parameters,an adaptive maximum correlated kurtosis deconvolution（AMCKD） method is proposed.The periodic modulation intensity（PMI） of envelope signal is used to identify the period of bearing fault impulses adaptively.Moreover,the period is constantly updated during searching for the optimal deconvolution filter iteratively,so that the real fault period is gradually approximated.Finally,the filtered signal with the largest correlated kurtosis is selected as the optimal deconvolution signal.Compared with MCKD method,AMCKD method can identify fault impulse period adaptively,avoid signal resampling process,and reduce the input parameters of the algorithm.Simulated and experimental results verify the effectiveness of this method in early fault feature extraction of rolling bearings,and the comparison with fast kurtogram method shows the superiority of AMCKD method in enhancing periodic impulse characteristics.…”
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New Robust Principal Component Analysis for Joint Image Alignment and Recovery via Affine Transformations, Frobenius and L2,1 Norms by Habte Tadesse Likassa

“…To solve the convex optimization involved, an alternating iterative process is also considered to alleviate the complexity. …”
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Joint recommendation algorithm based on tensor completion and user preference by Zhi XIONG, Kai XU, Lingru CAI, Weihong CAI

“…Aiming at the problem that existing recommendation algorithms have little regard for user preference,and the recommendation result is not satisfactory,a joint recommendation algorithm based on tensor completion and user preference was proposed.First,a user-item-category 3-dimensional tensor was built based on user-item scoring matrix and item-category matrix.Then,the Frank-Wolfe algorithm was used for iterative calculation to fill in the missing data of the tensor.At the same time,a user category preference matrix and a scoring preference matrix were built based on the 3-dimensional tensor.Finally,a joint recommendation algorithm was designed based on the completed tensor and the two preference matrices,and the differential evolution algorithm was used for parameter tuning.The experimental results show that compared with some typical and newly proposed recommendation algorithms,the proposed algorithm is superior to the compare algorithms,the precision is improved by 1.96% ~ 3.44% on average,and the recall rate is improved by 1.35%~2.40% on average.…”
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Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network by Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

“…For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.…”
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Direct localization algorithm of the aerial target based on external radiation source by Nan XIA, Danyang GAO, Baohui XING, Yaning WANG

“…In order to improve the accuracy of aerial target location and ensure its concealment, a direct location algo-rithm of the aerial target based on external radiation source was proposed.Fixed broadcast signals were used as transmit-ting sources, and the signals scattered by the aerial targets were received by multiple receivers.A direct relationship be-tween the synchronized multi-dimensional baseband signals and the position coordinates of the target was established, and then the spatial cross-spectrum function and joint matching function were constructed.Through iterative spectral peak search, the positioning results of the aerial target could be optimized, and the impact of direct signals and multipath signals on the ground could be effectively suppressed.Simulation results show that the performance of the proposed al-gorithm is better than that of the traditional two-step localization method and other direct localization methods in the case of low signal-to-noise ratio (SNR), and it can achieve high-precision localization of the three-dimensional mobile target.…”
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Creating, using, and sharing embodied information in the ultrarunning community on Instagram by Laura Williams, Andrew Cox, Andrea Jimenez

“…Ethnographic data was analysed as an iterative and reflexive process. Data collection, analysis, and writing are intertwined processes in the research design. …”
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A frequency offset compensation method based on all phase FFT amplitude by Yingjie ZHU, Wuxiong ZHANG, Huiyue YI, Hui XU

“…Distance measurement is an important part of the wireless location technology.The ranging accuracy of millimeter wave based distance measurement depends on the frequency estimation accuracy of beat signals from the targets, but the existing frequency estimation algorithms have the shortcomings of either high complexity or low accuracy.In order to improve the ranging accuracy, the frequency compensation value and frequency estimation method based on all phase FFT amplitude was proposed to improve the performance of frequency estimation.Firstly, the signal amplitude was estimated based on the relationship between its all phase FFT and its conventional FFT spectrum.Moreover, using the relationship between the estimated signal amplitude, the signal spectrum amplitude and frequency compensation value, the frequency compensation value was solved by Newton iterative algorithm.Then, the frequency compensation value was used to shift the frequency of the signal, and the frequency compensation value was estimated again to obtain the final estimation value of the signal frequency, from which the distance of the target was calculated.Finally, simulation results were presented to show that the proposed method has higher distance measurement accuracy than the existing methods.…”
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Fracture toughness of rough and frictional cracks emanating from a re-entrant corner by Andrea Carpinteri, Andrea Spagnoli, Michele Terzano, Sabrina Vantadori

“…The solution is found using the distributed dislocation method, and an iterative algorithm is needed due to the non-linearity of the model. …”
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Knowledge triple extraction in cybersecurity with adversarial active learning by Tao LI, Yuanbo GUO, Ankang JU

“…Aiming at the problem that using pipeline methods for extracting cybersecurity knowledge triples may cause the errors propagation of entity recognition and did not consider the correlation between entity recognition and relation extraction,and training triple extraction model lacked labeled corpora,an end-to-end cybersecurity knowledge triple extraction method with adversarial active learning was proposed.For knowledge triple extraction,the conventional entity recognition and relation extraction were modelled as sequence labeling task through joint labeling strategy firstly.And then,a BiLSTM-LSTM-based model with dynamic attention mechanism was designed to jointly extract entities and relations,forming triples.Finally,with adversarial learning framework,a discriminator was trained to incrementally select high-quality samples for labeling,and the performance of the joint extraction model was continuously enhanced by iterative retraining.Experiments show that the proposed joint extraction model outperforms the existing cybersecurity knowledge triple extraction methods,and demonstrate the effectiveness of proposed adversarial active learning scheme.…”
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Research on Complex Multiconstraint Path Planning Based on ACA Hybrid Algorithm by Hongyun Wang, Min Gao, Weiwei Gao, Wenzhao Li

“…The proposed model and planning algorithm are simulated based on the MATLAB platform environment, and it is shown by simulations that the hybrid algorithm has obvious advantages in terms of motion trajectory smoothness, number of iterations, and minimum path cost .It well solved the practical application problem of fast path planning convergence and fast avoiding obstacles in the complex environment.…”
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