Deconvolution via one-exponential Reference compound:

where:
I(t) is impulse response function of the sample;
g(t) is measured Instrumental response function (IRF);
f^ref(t) is measured one-exponential reference compound;
B(t) is measured background;
D  denotes the  time shift between sample decay and IRF;
b is time-uncorrelated background in the IRF or Reference compound;
g is background multiplication factor;
c is time-uncorrelated background in the sample decay;
n is scattered light coefficient;
t_ref  is decay time of reference compound;
are fit parameters and

d(t) is Dirac delta-function.
Complete deconvolution for analysis of multi-excitation decays is also supported.
The detailed protocol of the global analysis, programmed in TRFA Data Processor, is published in [4].

• Multi-exponential model for fluorescence decays
  
• Multi-exponential model for anisotropy decays
  
  The form of the multi-exponential model depends on the model property Fluor Parameters Type, which can be either “Amplitudes and decay times” or “Contributions and decay times” or “Ratio and decay times”. Switching between amplitudes and contributions is controlled by Normalization property of the multi-exponential model and can be done independently for positive and negative pre-exponential factors.
   
• Associative and non-associative models for anisotropy
  Two approaches for performing of anisotropy analysis are supported:
  1. Two stage anisotropy analysis based on a sequential fit of the measured sample total fluorescence decay and the measured sample parallel and perpendicular polarization components to the multi-exponential model. 
  2. The anisotropy analysis based on a direct global fit of the sample parallel and perpendicular polarization components. This approach also supports an associative anisotropy analysis. The fluorescence decay is calculated accordingly to the following equation:
  
  where A is the normalization parameter; a_j and t_j are, respectively, contributions and decay times of the corresponding fluorescence exponents; Q is the polarization angle, b_k and j_k are, respectively, the amplitudes and rotational correlation times of the corresponding anisotropy exponents and T_jk controls the associations.
   
• Two compartmental models
  
  

Fit parameters:
D  - the normalization parameter;
c_i  - the emission weighting factor of species i* (i=1,2);
b_i  - the concentration of species i* (i=1,2) at time zero;
k_0i - the composite rate constant of species i* (i=1,2);
k₁₂ - first-order rate constant for dissociation of 2* into 1* and co-reactant;
k₂₁ - second-order rate constant for the association of 1* and co-reactant to 2*.

• Three compartmental models
  
  

Fit parameters:
D  - the normalization parameter;
c_i  - the emission weighting factor of species i* (i=1,…,3);
b_i  - the concentration of species i* (i=1,…,3) at time zero;
k_0i - the composite rate constant of species i* (i=1,…,3);
k_1i - first-order rate constant for dissociation of i* (i=2,3) into 1* and co-reactant;
k_i1 - second-order rate constant for the association of 1* and co-reactant to i* (i=2,3).
k₂₃ - interconversion rate constant from state 3* to 2*;
k₃₂ - interconversion rate constant from state 2* to 3*.

• Poisson distribution of decay rates model
  

Fit parameters:
A  - the normalization parameter;
l₁ - the inverted decay time of first fluorescence component in absence of energy transfer or other quenching;
b₁ - quenching efficiency of first fluorescence component;
m  - average number of quenchers;
e  - rate of quenching for a probe interacting with one quencher;
a  - the relative contribution of second fluorescence component;
l₂ - the inverted decay time of second fluorescence component in absence of energy transfer or other quenching.

• Gaussian distribution of decay rates model
  

Fit parameters:
A  - the normalization parameter;
s - standard deviation on decay rate;
m  - average decay rate;
k₀  - minimum decay rate;
a  - the relative contribution of second fluorescence component;
l₂ - the inverted decay time of second fluorescence component.

        Modular object-oriented architecture allows for easy extension of the model library