[x,resnorm] = lsqcurvefit(___)

The `lsqcurvefit` function in MATLAB is used to fit a curve to a set of data points by minimizing the sum of the squared errors between the curve and the data points. The function takes in several input arguments, which are specified using the following syntax:

[x,resnorm] = lsqcurvefit(fun,x0,xdata,ydata)

where:

- `fun` is a function handle that defines the curve to be fitted. This function must take in the parameter vector `x` as its first argument, followed by the independent variable `xdata`. It should output a vector of predicted values that correspond to the elements of `xdata`.
- `x0` is an initial guess for the parameter vector `x`.
- `xdata` and `ydata` are the data points to which the curve is to be fitted. They should be vectors of the same length.

The output arguments of the function are:

- `x` is the vector of fitted parameters.
- `resnorm` is the sum of squared residuals between the predicted values and the actual data values.

In summary, `lsqcurvefit` is a powerful tool for curve fitting in MATLAB, allowing users to fit a wide range of mathematical functions to their data.