非线性回归代码matlab

Sure! Here's an example of non-linear regression code in MATLAB:

% Sample data
x = linspace(0, 10, 100)';
y = 2*sin(2*x) + randn(size(x));

% Non-linear regression model
model = @(beta, x) beta(1)*sin(beta(2)*x);

% Initial parameter guess
beta0 = [1, 1];

% Fit the model to the data
beta_hat = lsqcurvefit(model, beta0, x, y);

% Plot the original data and the fitted curve
plot(x, y, 'o')
hold on
plot(x, model(beta_hat, x))
hold off
xlabel('x')
ylabel('y')
legend('Data', 'Fitted curve')

In this code, we generate some sample data `x` and `y`. Then, we define a non-linear regression model using a function handle `model`. The model takes a parameter vector `beta` and the input variable `x` and returns the predicted output `y`.

We initialize the initial guess for the parameters `beta0`, and then use the `lsqcurvefit` function to fit the model to the data. Finally, we plot the original data points and the fitted curve using the estimated parameters.

Note that you may need to adjust the model function and the initial guess depending on your specific problem.