   In order to facilitate the usage of the Adaptive Filtering Toolbox, the authors have chosen to use a similar prototype 
for all the functions, whenever it was possible. Following we illustrate such prototype:

function    [outputVector,...
             errorVector,...
             coefficientVector] =   Affine_projection(desired,input,S)

where,

. desired: is the desired signal referred to as d(k) in [1]

. input: is the input signal referred to as x(k) in [1]

. outputVector: is the output of the adaptive filtering referred to as y(k) in [1]

. errorVector: is the error signal referred to as e(k) in [1]

. coefficientVector: is the impulse response of the adaptive filter referred to as w(k) in [1]

. S: is a structure in which the user sets specific parameters of the algorithm (in this case, the Affine_projection algorithm).



  For further details about a specific function, type: "help <function>"
Ex: > help Affine_projection


  If it is the first time using the toolbox it might be helpful to take a look at the example scripts, which provide simple 
system identification and channel equalization (in the case of blind algorithms) scenarios.


[1] P. S. R. Diniz, "Adaptive Filtering: Algorithms and Practical Implementation", 3rd Ed., Springer.  


