A New Supervised Learning Approach: Statistical Adaptive Fourier Decomposition (SAFD)

Tan, Chunyu; Zhang, Liming; Qian, Tao

doi:10.1007/978-3-030-36802-9_42

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…SAFD is one example. It can mean Stirring As Foam Disruption (Hoeks et al, 1997), Statistical Adaptive Fourier Decomposition (Tan et al, 2019) or Single Shot Anchor Free Face Detector (Wang et al, 2021). It relies largely on the context in which the entity is used to decide its contextual meaning and recommend its source paper.…”

Section: • Weighted Context Embedding-based Sorting Criterionmentioning

confidence: 99%

Detecting and analyzing missing citations to published scientific entities

Lin

Song

et al. 2022

Scientometrics

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Proper citation is of great importance in academic writing for it enables knowledge accumulation and maintains academic integrity. However, citing properly is not an easy task. For published scientific entities, the evergrowing academic publications and over-familiarity of terms easily lead to missing citations. To deal with this situation, we design a special method Citation Recommendation for Published Scientific Entity (CRPSE) based on the cooccurrences between published scientific entities and in-text citations in the same sentences from previous researchers. Experimental outcomes show the effectiveness of our method in recommending the source papers for published scientific entities. We further conduct a statistical analysis on missing citations among papers published in prestigious computer science conferences in 2020. In the 12,278 papers collected, 475 published scientific entities of computer science and mathematics are found to have missing citations. Many entities mentioned without citations are found to be well-accepted research results. On a median basis, the papers proposing these published scientific entities with missing citations were published 8 years ago, which can be considered the time frame for a published scientific entity to develop into a wellaccepted concept. For published scientific entities, we appeal for accurate and full citation of their source papers as required by academic standards.

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Section: • Weighted Context Embedding-based Sorting Criterionmentioning

confidence: 99%

Detecting and analyzing missing citations to published scientific entities

Lin

Song

et al. 2022

Scientometrics

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“…Fourier series allows for a periodic expansion of individual elements of physiological signals [45][46][47]. In such approach, individual elements of ECG signal may be determined via a system of the mathematical equations, and consequently expanded into the Fourier series [48,49]. The further approach for the modeling utilizes a system of ordinary differential equations, in which user should define the characteristics of the heart rate [50][51][52].…”

Section: Recent Workmentioning

confidence: 99%

An Artificial Heart System for Testing and Evaluation of Cardiac Pacemakers

Augustýnek¹,

Kubicek²,

Thomas³

et al. 2022

Computers, Materials &Amp; Continua

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The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary. This paper provides the outcomes of development and complex testing of the artificial cardiac system to evaluate the pacemaker's functionality. In this work, we used the modular laboratory platform ELVIS II and created graphical user interface in LabVIEW programming environment. The electrical model of the heart allows signals generation (right atrium, right ventricle) and the monitoring of the stimulation pulses. The LabVIEW user interface allows to set the parameters of the generated signals and the simulation of the cardiac rhythm disorders as well as the monitoring and visualization of the pacemaker behavior in real-time. The results demonstrate the capability of proposed system to evaluate the paced and sensed pulses. The proposed solution allows the scientists to test the behavior of any cardiac pacemaker for its pre-programmed settings and pacing mode. In addition, the proposed system can simulate various disorders and test cardiac pacemakers in different working modes.

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“…The necessity of developing a theory in the general Hilbert space context lays in the demanding of applications, especially in the multivariate RS cases, in which there do not exist analyticity properties as being used in the classical Hardy space cases. As example, by using the developed sparse representation algorithm one may analyze heart ECG signals from a group of people at one time, [6][7][8] or numerically or with explicit formulas, solve certain stochastic partial differential equations. 9 For the reader's convenience, we give the following abbreviations list…”

Section: Qianmentioning

confidence: 99%

Sparse representations of random signals

Qian

2021

Math Methods in App Sciences

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Sparse (fast) representations of deterministic signals have been well studied. Among other types, there exists one called adaptive Fourier decomposition (AFD) for functions in analytic Hardy spaces. Through the Hardy space decomposition of the L 2 -space, the AFD algorithm also gives rise to sparse representations of signals of finite energy. To deal with multivariate signals, the general Hilbert space context comes into play. The multivariate counterpart of AFD in general Hilbert spaces with a dictionary has been named preorthogonal AFD (POAFD). In the present study, we generalize AFD and POAFD to random analytic signals through formulating stochastic analytic Hardy spaces and stochastic Hilbert spaces. To analyze random analytic signals, we work on two models, both being called stochastic AFD, or SAFD in brief. The two models are respectively made for (i) those expressible as the sum of a deterministic signal and an error term (SAFDI) and for (ii) those from different sources obeying certain distributive law (SAFDII). In the later part of the paper, we drop off the analyticity assumption and generalize the SAFDI and SAFDII to what we call stochastic Hilbert spaces with a dictionary. The generalized methods are named as stochastic POAFDs, SPOAFDI and SPOAFDII. Like AFDs and POAFDs for deterministic signals, the developed stochastic POAFD algorithms offer powerful tools to approximate and thus to analyze random signals.

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A New Supervised Learning Approach: Statistical Adaptive Fourier Decomposition (SAFD)

Cited by 4 publications

References 11 publications

Detecting and analyzing missing citations to published scientific entities

Detecting and analyzing missing citations to published scientific entities

An Artificial Heart System for Testing and Evaluation of Cardiac Pacemakers

Sparse representations of random signals

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