自动寻峰算法（matlab源文件）

Menu of peak shape numbers: Gaussians: y=exp(-((x-pos)./(0.6005615.*width)) .^2) Gaussians with independent positions and widths : 1 (default) Exponentional-broadened Gaussian (equal time constants): 5 Exponentional-broadened equal-width Gaussian : 8 Fixed-width exponentionally-broadened Gaussian = 36 Exponentional-broadened Gaussian (independent time constants): 31 Gaussians with the same widths : 6 Gaussians with preset fixed widths : 11 Fixed-position Gaussians : 16 Asymmetrical Gaussians with unequal half-widths on both sides : 14 Lorentzians: y=ones(size(x))./(1+((x-pos)./(0.5.*width)).^2) Lorentzians with independent positions and widths : 2 Exponentional-broadened Lorentzian : 18 Equal-width Lorentzians : 7 Fixed-width Lorentzian : 12 Fixed-position Lorentzian : 17 Asymmetrical Lorentzians with unequal half-widths on both sides : 15 Gaussian/Lorentzian blend (equal blends): 13 Fixed-width Gaussian/Lorentzian blend : 35 Gaussian/Lorentzian blend with independent blends): 33 Voigt profile with equal alphas): 20 Fixed-width Voigt profile with equal alphas : 34 Voigt profile with independent alphas : 30 Logistic: n=exp(-((x-pos)/(.477.*wid)).^2); y=(2.*n)./(1+n) : 3 Pearson: y=ones(size(x))./(1+((x-pos)./((0.5.^(2/m)).*wid)).^2).^m : 4 Fixed-width Pearson = 37 Pearson with independent shape factors, m : 32 Exponential pulse: y=(x-tau2)./tau1.*exp(1-(x-tau2)./tau1) : 9 Alpha function: y=(x-spoint)./pos.*exp(1-(x-spoint)./pos); : 19 Up Sigmoid (logistic function): y=.5+.5*erf((x-tau1)/sqrt(2*tau2)) : 10 Down Sigmoid y=.5-.5*erf((x-tau1)/sqrt(2*tau2) ): 23 Triangular : 21