curve fitting

This tutorial covers curve fitting using cubic numerator and quadratic denominator in Matlab.

This resource demonstrates the use of Least Squares Method to fit a circle curve. The output includes the coordinates of the center and the radius of the fitted circle.

This document provides data and code for analyzing and generating graphs related to the E. coli pulse/saturation project. The provided MATLAB and Python codes are designed for pulse feeding analysis and were written in MATLAB R2015b. If you use any of the data or code, please cite the following paper: Karthik Sekar, Roberto Rusconi, John T Sauls, Tobias Fuhrer, Elad Noor, Jen Nguyen, Vicente I Fernandez, Marieke F Buffing, Michael Berney, Suckjoon Jun, Roman Stocker, Uwe Sauer. Molecular Systems Biology, 2018; 14(11): e8623. Published on November 5, 2018. DOI: 10.15252/msb.20188623. The repository is divided into the following sections: Part 1 - Data and Analysis of Lag Time vs. Feeding FrequencyThis section contains all the OD data and code for the wild-type pulse experiments. The code generates the following graphs:- All OD vs. Time plots with linear threshold fitting.- Relationship between lag time, feeding rate, and linear growth rate.- Summary table for the total glucose needed for proliferation and feeding speed. Part 2 - Flow Cytometry

该工具箱包含了各种绘制NURBS曲线和NURBS曲面的程序。对于从事曲面设计或相关领域的工作者来说，非常有用；同时，也为学习MATLAB编程提供了强大的支持，帮助用户更好地掌握该语言的应用。

针对一组x，y值的基于最小平方方差和的椭圆和圆的拟合，用Matlab实现。

MATLAB非线性拟合课件，教你怎样熟练运用MATLAB进行非线性拟合处理。

l-曲线 MATLAB 代码与 cgDNA：DNA的序列依赖性粗粒模型的实现方法，通过模拟 DNA 序列的特征，深入分析其结构和功能。该模型不仅能够有效展示 DNA 的复杂性，还提供了对序列变化的灵敏响应，便于科研人员进行进一步研究和探索。

在使用Matlab拟合工具箱处理试验数据时，首先需要导入数据。可以使用以下代码示例： load('data.mat'); % 导入数据 x = data(:,1); % 自变量 y = data(:,2); % 因变量 接下来，使用fit函数来进行拟合。例如，若要拟合一个线性模型： ft = fit(x, y, 'poly1'); % 线性拟合 通过plot函数可以可视化拟合结果： plot(ft, x, y); % 绘制拟合曲线与原始数据 使用Matlab拟合工具箱的优势在于其图形界面友好，适合初学者。此外，工具箱支持多种拟合类型，如多项式拟合、指数拟合等，使得数据处理更加灵活。

This MATLAB example demonstrates the use of gradient descent to iteratively solve for the coefficients of a noisy quadratic curve. The algorithm is applied to fit a quadratic curve model, and the noisy data points are used to estimate the optimal coefficients through gradient descent optimization. This example is designed to inspire and help others understand how gradient descent can be applied in real-world curve fitting problems.

故可制定给药方案：即:首次注射375mg，其余每次注射225mg，注射的间隔时间为4小时。