fs = 1000;
t = 0:1/fs:14-1/fs;

sig = [chirp(t-1,0.1,17,2,'quadratic',1).*sin(2*pi*t/5);
    chirp(t-2,2,2,2.1,'quadratic',100).*exp(-(t-6.5).^2/20).*sin(2*pi*t*2);
    0.85*besselj(0,5*(sin(2*pi*(t+1.5).^2/20).^2)).*sin(2*pi*t/9)]';

sigsat = sig;
stv = 0.1;
sigsat(sigsat >= stv) = stv;

function [y,tOut] = declip(x,tIn,varargin)
% Declip saturated signal by fitting a polynomial

    % Initialize the output signal

    y = x;

    % For signals with no time information, use sample numbers as abscissas
    
    if isempty(tIn)
        tOut = [];
        t = (1:length(x))';
    else
        t = tIn;
        tOut = t;
    end
    
    % Specify the degree of the polynomial as an optional input argument
    % and provide a default value of 4
    
    if nargin<3
        ndx = 4;
    else
        ndx = varargin{1};
    end

    % To implement your algorithm, you can use any MATLAB or Signal
    % Processing Toolbox function
    
    % Find the intervals where the signal is saturated and generate an 
    % array containing the interval endpoints
    idx = find(x==max(x)); 
    fir = [true;diff(idx)~=1];
    ide = [idx(fir) idx(fir([2:end 1]))];
    % For each interval, fit a polynomial of degree ndx over the ndx+1 points
    % before the interval and the ndx+1 points after the interval
    for k = 1:size(ide,1)
        bef = ide(k,1); aft = ide(k,2);
        intv = [bef-1+(-ndx:0) aft+1+(0:ndx)];
        [pp,~,mu] = polyfit(t(intv),x(intv),ndx);
        y(bef:aft) = polyval(pp,t(bef:aft),[],mu);
    end

end