Model-independent Method Research Articles

In vitro comparative quality evaluation of different brands of Amlodipine Tablets Commercially available in Jimma Town, South-western Ethiopia.

The incidence of hypertension in persons 25 years of age and older is estimated to be 46% in Africa, where it is still very common. This concerning rate could be explained by the pharmaceutical markets' accessibility to poor quality antihypertensive drugs. Thus, the purpose of this study was to evaluate and compare the quality different brands of Amlodipine Tablets Commercially available in Jimma Town, South-western Ethiopia. The quality control test was conducted from August 30, 2019 to February 27, 2020 at Jimma University in the Laboratory of Drug Quality Control (JuLaDQ). The laboratory test was carried out in accordance with WHO inspection guidelines and United States Pharmacopeia. A statistically significant was considered when P<0.05. For further comparison of the in-vitro dissolution profiles of amlodipine tablets, model-independent model-dependent parameters and statistical Dunnetts tests for ensuring bioequivalence were used to further compare the in-vitro dissolution profiles. With the exception of brand AMD-5 (1/10), the remaining nine (n = 9) brands were within WHO visual inspection criteria. The quality control parameters such as friability, weight variation, identity, assay, and dissolution test were within the United States Pharmacopeia. The model independent parameters (f1, and f2) confirmed that, all generic products were bio-equivalence, and interchangeable with comparator product. The model dependent approaches revealed the Weibull model (AMD-10), the Zero order (AMD-3), and the Korsemeyer-Peppas models were the most effective predictions for the release of the pharmaceutical substance from the dosage form. The Korsemeyer-Peppas model (r2 ≥0.9695) was the best descriptive model for determining the amlodipine drug kinetics from the point of view of all brands examined. The evaluated amlodipine brand tablets were in line with quality standards. The model independent methods confirmed that the generic brand tablets were interchangeable in clinical practice. The tested products follow more than two drug release kinetics. The study revealed a manifest discrepancy in the dissolution profiles' releases. Therefore, it is strongly advised to use appropriately designed dissolution profile evaluation methods with various pH values in the dissolution media, as well as to do comprehensive visual inspections. This will make it easier to do a thorough investigation of any potential quality issues that might be related to various generic products available in the pharmaceutical market.

Separating the Spectral Counterparts in NGC 1275/Perseus Cluster in X-Rays

We present a model-independent method for separating the spectral counterparts of the active galactic nucleus (AGN) NGC 1275 from the surrounding emission of the Perseus cluster, as observed by Suzaku/XIS cameras. The Perseus cluster emission extends to higher energies than typically observed in AGN environments, reaching up to 9–10 keV. This necessitates precise separation of AGN and cluster spectra. To circumvent the degeneracy arising from numerous spectral fitting parameters, including elemental abundances, thermal and Compton emissions from the nucleus, and spectral parameters of the jet synchrotron self-Compton/inverse Compton emissions, we avoid traditional spectral fitting methods. Instead, we leverage spatial resolution and employ a double background subtraction approach. We apply this procedure to the complete set of Suzaku/XIS observational data for NGC 1275, resulting in cleaned spectra and a light curve of the AGN emission in this system. To demonstrate the applicability of our method, we also utilize the available XMM-Newton/EPIC data.

Model-independent extrapolation of MUonE data with Padé and D-Log approximants

The MUonE experiment is designed to extract the hadronic contribution to the electromagnetic coupling in the spacelike region Δαhad(t) from elastic eμ scattering. The leading-order hadronic vacuum polarization contribution to the muon g−2, aμHVP,LO, can then be obtained from a weighted integral over Δαhad(t). This, however, requires knowledge of Δαhad(t) in the whole domain of integration, which cannot be achieved by experiment. In this work, we propose to use Padé and D-Log Padé approximants as a systematic and model-independent method to fit and reliably extrapolate the future MUonE experimental data, extracting aμHVP,LO with a conservative but competitive uncertainty, using no or very limited external information. The method relies on fundamental analytic properties of the two-point correlator underlying aμHVP,LO and provides lower and upper bounds for the result for aμHVP,LO. We demonstrate the reliability of the method using toy datasets generated from a model for Δαhad(t) reflecting the expected statistics of the MUonE experiment. Published by the American Physical Society 2024

Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using ensemble rainfall–runoff analysis (ERRA): proof of concept

Abstract. A classical approach to understanding hydrological behavior is the unit hydrograph and its many variants, but these often assume linearity (runoff response is proportional to effective precipitation), stationarity (runoff response to a given unit of rainfall is identical, regardless of when it falls), and spatial homogeneity (runoff response depends only on spatially averaged precipitation). In the real world, by contrast, runoff response is typically nonlinear, nonstationary, and spatially heterogeneous. Quantifying this nonlinearity, nonstationarity, and spatial heterogeneity is essential to unraveling the mechanisms and subsurface properties controlling hydrological behavior. Here, I present proof-of-concept demonstrations illustrating how nonlinear, nonstationary, and spatially heterogeneous rainfall–runoff behavior can be quantified, directly from data, using ensemble rainfall–runoff analysis (ERRA), a data-driven, model-independent method for quantifying rainfall–runoff relationships across a spectrum of time lags. I show how ERRA uses nonlinear deconvolution to quantify how catchments' runoff responses vary with precipitation intensity and to estimate their precipitation-weighted runoff response distributions. I further illustrate how ERRA combines nonlinear deconvolution with de-mixing techniques to reveal how runoff response depends jointly on precipitation intensity and nonstationary ambient conditions, including antecedent wetness and vapor pressure deficit. I demonstrate how ERRA's de-mixing techniques can be used to quantify spatially heterogeneous runoff responses in different parts of a catchment, even if those subcatchments are not separately gauged. I also illustrate how ERRA's broken-stick deconvolution capabilities can be used to quantify multiscale runoff responses that combine hydrograph peaks lasting for hours and recessions lasting for weeks, well beyond the average spacing between storms. ERRA can unscramble these multiple effects on runoff response even if they are overprinted on each other through time and even if they are corrupted by autoregressive moving average (ARMA) noise. Results from this approach may be informative for catchment characterization, process understanding, and model–data comparisons; they may also lead to a better understanding of storage dynamics and landscape-scale connectivity. An R script is provided to perform the necessary calculations, including uncertainty analysis.

Encyclopædia Inflationaris: Opiparous Edition

The current flow of high-accuracy astrophysical data, among which are the Cosmic Microwave Background (CMB) measurements by the Planck satellite, offers an unprecedented opportunity to constrain the inflationary theory. This is however a challenging project given the size of the inflationary landscape which contains hundreds of different scenarios. Given that there is currently no observational evidence for primordial non-Gaussianities, isocurvature perturbations or any other non-minimal extension of the inflationary paradigm, a reasonable approach is to consider the simplest models first, namely the slow-roll single-field models with minimal kinetic terms. This still leaves us with a very populated landscape, the exploration of which requires new and efficient strategies. It has been customary to tackle this problem by means of approximate model-independent methods while a more ambitious alternative is to study the inflationary scenarios one by one. We have developed the publicly available runtime library ASPIC11https://github.com/cosmicinflation/aspic. to implement this last approach. The ASPIC code provides all routines needed to quickly derive reheating-consistent observable predictions within this class of scenarios. ASPIC has been designed as an evolutive code which presently supports 118 different models. In this paper, for each of the ASPIC models, we present and collect new results in a systematic manner, thereby constituting the first Encyclopædia Inflationaris.

Comparative Study of Itopride Hydrochloride in-Vitro Drug Release in Various Brands of Sustained Release Capsules By RP-HPLC

Background: The World Health Organisation has advocated the use of generic medicines to make them accessible and affordable but studies have revealed that marketed products do not produce same therapeutic effects and hence are not interchangeable. Dissolution testing of generic solid dosage forms serves as a valuable tool for acquiring dissolution profiles and for assessing the similarity or dissimilarity between the formulations under examination. Objectives: To evaluate the in-vitro drug release profiles of different generic brands of Itopride Sustained release capsules that are commercially available in Indian market and compare them with the innovator product using model dependant and as well as model independent methods. To determine whether same medicine manufactured by different brands are interchangeable. Materials &amp; Methods: In this study Eight generic brands of Itopride 150mg sustained release capsules available in the Indian market were evaluated using dissolution test with the aim to assess their bioequivalence with the innovator product (Ganaton OD). Dissolution studies were performed using USP type II apparatus at 100 rpm in 900 ml 0.1N HCl while maintaining a temperature of 37±0.5 ºC. The samples were estimated by a validated HPLC method. Dissolution test results were statistically evaluated by employing both model dependant and model independent methods. In model dependant experimental data obtained for each dissolution profile were transformed by applying the equations of different kinetic models and the best-fit model was selected whereas in model independent approach fit factors, dissolution efficiency and mean dissolution times were calculated. Results: The Weibull model best explained the release of drugs from all the brands. Upon statistical evaluation of dissolution test results its was found that while similarity factor f2 was within the limits for all generic brands, difference factor f1 of two brands was out of acceptable range thus questioning their bioequivalency with the innovator product. Also the dissolution efficiency of four out of the brands was out of acceptable limits. Keywords: bioequivalence, difference factor (f1), similarity factor (f2), dissolution profile, comparison and evaluation..

Pathfinding Pulsar Observations with the CVN Incorporating the FAST

Abstract The importance of Very Long Baseline Interferometry (VLBI) for pulsar research is becoming increasingly prominent and receiving more and more attention. We present the pathfinding pulsar observation results with the Chinese VLBI Network (CVN) incorporating the Five-hundred-meter Aperture Spherical radio Telescope (FAST). On MJD 60045 (11th April 2023), PSRs B0919+06 and B1133+16 were observed with the phase-referencing mode in the L-band using four radio telescopes (FAST, TianMa, Haoping, and Nanshan) and correlated with the pulsar binning mode of the distributed FX-style software correlator in Shanghai. After further data processing with the NRAO Astronomical Image Processing System (AIPS), we detected these two pulsars and fitted their current positions with accuracy at the milliarcsecond level. By comparison, our results show significantly better agreement with predicted values based on historical VLBI observations than those with previous timing observations, as pulsar astrometry with the VLBI provides a more direct and model-independent method for accurately obtaining related parameters.

Quantifying decision support level of explainable automatic classification of diagnoses in Spanish medical records

Background and Objective:In the realm of automatic Electronic Health Records (EHR) classification according to the International Classification of Diseases (ICD) there is a notable gap of non-black box approaches and more in Spanish, which is also frequently ignored in clinical language classification. An additional gap in explainability pertains to the lack of standardized metrics for evaluating the degree of explainability offered by distinct techniques. Methods:We address the classification of Spanish electronic health records, using methods to explain the predictions and improve the decision support level. We also propose Leberage a novel metric to quantify the decision support level of the explainable predictions.We aim to assess the explanatory ability derived from three model-independent methods based on different theoretical frameworks: SHapley Additive exPlanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), and Integrated Gradients (IG). We develop a system based on longformers that can process long documents and then use the explainability methods to extract the relevant segments of text in the EHR that motivated each ICD. We then measure the outcome of the different explainability methods by implementing a novel metric. Results:Our results beat those that carry out the same task by 7%. In terms of explainability degree LIME appears as a stronger technique compared to IG and SHAP. Discussion:Our research reveals that the explored techniques are useful for explaining the output of black box models as the longformer. In addition, the proposed metric emerges as a good choice to quantify the contribution of explainability techniques.

Estimating data complexity and drift through a multiscale generalized impurity approach

The quality of machine learning solutions, and of classifier models in general, depend largely on the performance of the chosen algorithm, and on the intrinsic characteristics of the input data. Although work has been extensive on the former of these aspects, the latter has received comparably less attention. In this paper, we introduce the Multiscale Impurity Complexity Analysis (MICA) algorithm for the quantification of class separability and decision-boundary complexity of datasets. MICA is both model and dimensionality-independent and can provide a measure of separability based on regional impurity values. This makes it so that MICA is sensible to both global and local data conditions. We show MICA to be capable of properly describing class separability in a comprehensive set of both synthetic and real datasets and comparing it against other state-of-the-art methods. After establishing the robustness of the proposed method, alternative applications are discussed, including a streaming-data variant of MICA (MICA-S), that can be repurposed into a model-independent method for concept drift detection.

Accurate and Model-independent Radius Determination of Single FGK and M Dwarfs Using Gaia DR3 Data

Measuring fundamental stellar parameters is key to fully comprehending the evolution of stars. However, current theoretical models overpredict effective temperatures, and underpredict radii, compared to observations of K and M dwarfs (radius inflation problem). In this work, we have developed a model-independent method to infer precise radii of single FGK and M dwarfs using Gaia DR3 parallaxes and photometry, and used it to study the radius inflation problem. We calibrated nine surface brightness–color relations for the three Gaia magnitudes and colors using a sample of stars with angular diameter measurements. We achieved an accuracy of 4% in our angular diameter estimations, which Gaia’s parallaxes allow us to convert to physical radii. We validated our method by comparing our radius measurements with literature samples and the Gaia DR3 catalog, which confirmed the accuracy of our method and revealed systematic offsets in the Gaia measurements. Moreover, we used a sample with measured Hα equivalent width (Hα EW), a magnetic activity indicator, to study the radius inflation problem. We demonstrated that active stars have larger radii than inactive stars, showing that radius inflation is correlated with magnetic activity. We found a correlation between the radius inflation of active stars and Hα EW for the mass bin 0.5 < M[M ⊙] ≤ 0.6, but we found no correlation for lower masses. This could be due to lack of precision in our radius estimation or a physical reason. Radius measurements with smaller uncertainties are necessary to distinguish between the two scenarios.

Model-independent extraction of form factors and |Vcb| in B¯→Dℓ−ν¯ℓ with hadronic tagging at BABAR

Using the entire ϒ(4S) dataset, the first two-dimensional unbinned angular analysis of the semileptonic decay B¯→Dℓ−ν¯ℓ is performed, employing hadronic reconstruction of the tag-side B meson from ϒ(4S)→BB¯. Here, ℓ denotes the light charged leptons e and μ. A novel data-driven signal-background separation procedure with minimal dependence on simulation is developed. This procedure preserves all multidimensional correlations present in the data. The expected sin2θℓ dependence of the differential decay rate in the Standard Model is demonstrated, where θℓ is the lepton helicity angle. Including input from the latest lattice QCD calculations and previously available experimental data, the underlying form factors are extracted using both model-independent (BGL) and dependent (CLN) methods. Comparisons with lattice calculations show flavor SU(3) symmetry to be a good approximation in the B(s)→D(s) sector. Using the BGL results, the CKM matrix element |Vcb|=(41.09±1.16)×10−3 and the Standard Model prediction of the lepton-flavor universality violation variable R(D)=0.300±0.004, are extracted. The value of |Vcb| from B¯→Dℓ−ν¯ℓ tends to be higher than that extracted using B¯→D*ℓ−ν¯ℓ. The Standard Model R(D) calculation is at a 1.97σ tension with the latest HFLAV experimental average. Published by the American Physical Society 2024

Identification of exon regions in eukaryotes using fine-tuned variational mode decomposition based on kurtosis and short-time discrete Fourier transform

In genomic research, identifying the exon regions in eukaryotes is the most cumbersome task. This article introduces a new promising model-independent method based on short-time discrete Fourier transform (ST-DFT) and fine-tuned variational mode decomposition (FTVMD) for identifying exon regions. The proposed method uses the N/3 periodicity property of the eukaryotic genes to detect the exon regions using the ST-DFT. However, background noise is present in the spectrum of ST-DFT since the sliding rectangular window produces spectral leakage. To overcome this, FTVMD is proposed in this work. VMD is more resilient to noise and sampling errors than other decomposition techniques because it utilizes the generalization of the Wiener filter into several adaptive bands. The performance of VMD is affected due to the improper selection of the penalty factor (α), and the number of modes (K). Therefore, in fine-tuned VMD, the parameters of VMD (K and α) are optimized by maximum kurtosis value. The main objective of this article is to enhance the accuracy in the identification of exon regions in a DNA sequence. At last, a comparative study demonstrates that the proposed technique is superior to its counterparts.

A model-independent tripartite test of cosmic distance relations

Cosmological distances are fundamental observables in cosmology. The luminosity (D L), angular diameter (D A) and gravitational wave (D GW) distances are all trivially related in General Relativity assuming no significant absorption of photons in the extragalactic medium, also known as cosmic opacity. Supernovae have long been the main cosmological standard candle, but bright standard sirens are now a proven alternative, with the advantage of not requiring calibration with other astrophysical sources. Moreover, they can also measure deviations from modified gravity through discrepancies between D L and D GW. However, both gravitational and cosmological parameters are degenerate in the Hubble diagram, making it hard to properly detect beyond standard model physics. Finally, recently a model-independent method named FreePower was proposed to infer angular diameter distances from large-scale structure which is independent of the knowledge of both early universe and dark energy physics. In this paper we propose a tripartite test of the ratios of these three distances with minimal amount of assumptions regarding cosmology, the early universe, cosmic opacity and modified gravity. We proceed to forecast this test with a combination of LSST and Roman supernovae, Einstein Telescope bright sirens and a joint DESI-like + Euclid-like galaxy survey. We find that even in this very model-independent approach we will be able to detect, in each of many redshift bins, percent-level deviations in these ratios of distances, allowing for very precise consistency checks of ΛCDM and standard physics. It can also result in sub-percent measurements of H 0.

Extended uncertainty principle: A deeper insight into the Hubble tension?

The standard cosmological model, known as the ΛCDM model, has been successful in many respects, but it has some significant discrepancies, some of which have not been resolved yet. In measuring the Hubble-Lemaître parameter, there is an apparent discrepancy which is known as the Hubble tension, defined as differences in values of this parameter measured by the Type Ia Supernovae (SNeIa) data (a model-independent method) and by the Cosmic Microwave Background (CMB) radiation maps (a model-dependent method). Although many potential solutions have been proposed, the issue still remains unresolved. Recently, it was observed that the Hubble tension can be due to the concept of uncertainty in measuring cosmological parameters at large distance scales through applying the Heisenberg Uncertainty Principle (HUP) in cosmological setups. Extending this pioneering idea, in the present study we plan to incorporate the Extended Uncertainty Principle (EUP) containing a minimal fundamental measurable momentum (or equivalently, a maximal fundamental measurable length) as a candidate setup for describing large-scale effects of Quantum Gravity (QG) to address the Hubble tension and constrain the EUP length scale. In this regard, by finding a relevant formula for the effective photon rest mass in terms of the present-time value of the Hubble-Lemaître parameter, we see that discrepancies in the value of photon rest mass associated with the Hubble-Lemaître parameter values estimated from model-independent and model-dependent methods perhaps is the cause of Hubble tension. We show explicitly that the presence of a non-zero minimal uncertainty in momentum (or non-zero maximal uncertainty in position) measurements as a consequence of the large distance quantum gravity effect addresses the Hubble tension satisfactorily without having to invoke new physics. Moreover, we use the formula for the effective photon rest mass to find some relevant lower bounds on the EUP length scale.

Model Independent and Dependent Methods for Dissolution Profiles Comparison: Can we take the Road Less Travelled?

Dissolution testing plays an important role in pharmaceutical development due to its ability to provide critical insight into in vivo performance. Dissolution testing during routine pharmaceutical development can ensure batch-to-batch consistency and helps to ensure that the commercial batches are of representative quality to that of studied in the pivotal clinical studies. For comparing the dissolution profiles, there are multitude of approaches suggested by various regulatory agencies that consist of model independent and dependent approaches. The present review aims to summarize the current understanding of dissolution profile similarity approaches. Dissolution profile comparison approaches suggested by various regulatory agencies were compared and contrasted. Further, detailed procedural aspects were provided for the determination of similarity using model independent and dependent approaches. Model independent approaches such as f2 bootstrap, and Multivariate Statistical Distance (MSD) were portrayed from a practical perspective. Advanced tools such as Bias-Corrected and accelerated (BCa) for f2 bootstrap were discussed in depth. Further, model dependent approaches such as zero order, and Weibull models were discussed from realistic scenarios. Finally, the utility of modeling and simulation approaches such as physiologically based pharmacokinetics model (PBPK) and physiologically based biopharmaceutics model (PBBM) were discussed in the context of their ability and potential to supersede traditional dissolution dissimilarity. Overall, this article acts as a ready-to-use guide for pharmaceutics and biopharmaceutics scientists for effective methodologies for dissolution profile comparison for internal decision-making and regulatory justifications.

Cluster Scanning: a novel approach to resonance searches

We propose a new model-independent method for new physics searches called Cluster Scanning. It uses the k-means algorithm to perform clustering in the space of low-level event or jet observables, and separates potentially anomalous clusters to construct a signal-enriched region. The spectra of a selected observable (e.g. invariant mass) in these two regions are then used to determine whether a resonant signal is present. A pseudo-analysis on the LHC Olympics dataset with a Z′ resonance shows that Cluster Scanning outperforms the widely used 4-parameter functional background fitting procedures, reducing the number of signal events needed to reach a 3σ significant excess by a factor of 0.61. Emphasis is placed on the speed of the method, which allows the test statistic to be calibrated on synthetic data.

Governing accelerating Universe via newly reconstructed Hubble parameter by employing empirical data simulations

A new parametrization of the Hubble parameter is proposed to explore the issue of the cosmological landscape. The constraints on model parameters are derived through the Markov Chain Monte Carlo (MCMC) method by employing a comprehensive union of datasets such as 34 data points from cosmic chronometers (CC), 42 points from baryonic acoustic oscillations (BAO), a recently updated set of 1701 Pantheon+ (P22) data points derived from Type Ia supernovae (SNeIa), and 162 data points from gamma-ray bursts (GRBs). Furthermore, the models are compared by using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), so that a comparative assessment of model performance can be available. Additionally, we compare the Dainotti relation via Gaussian likelihood analysis versus new likelihoods and Calibration of the Dainotti relation through a model-independent method. The kinematic behavior of the models is also investigated by encompassing the transition from deceleration to acceleration and the evolution of the jerk parameter. From the analysis of the parametric models, it is strongly indicated that the Universe is currently undergoing an accelerated phase with diagnostics of the model validating the quintessence phase.

Multiple measurements on the cosmic curvature using Gaussian process regression without calibration and a cosmological model

In this letter, we propose a novel cosmological model-independent method to determine cosmic curvature, combining the recent measurements of transverse and line-of-sight directions in the baryon acoustic oscillations (BAO) with cosmic chronometers (CC) datasets. Considering that the CC dataset is discrete and includes only 32 H(z) measurements, we apply Gaussian process (GP) regression to fit the CC dataset and reconstruct them. Our methodology, which does not need the calibration or selection of any cosmological model, provide multiple measurements of spatial curvature (ΩK) at different redshifts (depending on the redshift coverage of BAO dataset). For combination of all BAO data, we find that the constraint result on cosmic curvature is ΩK=−0.096−0.195+0.190 with 1σ observational uncertainty. Although the measured ΩK is in good agreement with zero cosmic curvature within 1σ confidence level, our result revels the fact of a closed universe. More importantly, our results show that the obtained ΩK measurements are almost unaffected by different priors of the Hubble constant. This could help solve the issue of the Hubble tension that may be caused by inconsistencies in the spatial curvature between the early and late universes.

Adaptive variational low-rank dynamics for open quantum systems

We introduce a model-independent method for the efficient simulation of low-entropy systems, whose dynamics can be accurately described with a limited number of states. Our method leverages the time-dependent variational principle to efficiently integrate the Lindblad master equation, dynamically identifying and modifying the low-rank basis over which we decompose the system's evolution. By dynamically adapting the dimension of this basis, and thus the rank of the density matrix, our method maintains optimal representation of the system state, offering a substantial computational advantage over existing adaptive low-rank schemes in terms of both computational time and memory requirements. We demonstrate the efficacy of our method through extensive benchmarks on a variety of model systems, with a particular emphasis on multiqubit bosonic codes, a promising candidate for fault-tolerant quantum hardware. Our results highlight the method's versatility and efficiency, making it applicable to a wide range of systems characterized by arbitrary degrees of entanglement and moderate entropy throughout their dynamics. We provide an implementation of the method as a Julia package, making it readily available to use. Published by the American Physical Society 2024

A Distortion Correction Method Based on Actual Camera Imaging Principles.

In the human-robot collaboration system, the high-precision distortion correction of the camera as an important sensor is a crucial prerequisite for accomplishing the task. The traditional correction process is to calculate the lens distortion with the camera model parameters or separately from the camera model. However, in the optimization process calculate with the camera model parameters, the mutual compensation between the parameters may lead to numerical instability, and the existing distortion correction methods separated from the camera model are difficult to ensure the accuracy of the correction. To address this problem, this study proposes a model-independent lens distortion correction method based on the image center area from the perspective of the actual camera lens distortion principle. The proposed method is based on the idea that the structured image preserves its ratios through perspective transformation, and uses the local image information in the central area of the image to correct the overall image. The experiments are verified from two cases of low distortion and high distortion under simulation and actual experiments. The experimental results show that the accuracy and stability of this method are better than other methods in training and testing results.