Adaptive EQ Compare QAM/VSB

I need to compare two communications techniques for speed of equalizer convergence in a time varing channel. To this end, as a deliverable, you should supply all Matlab functions (*.m) to setup and intialize the equalizers and to process an input sample (with both input and desired output - for training section of the data frame - and just random signal data). The first system is a QAM system (with programmable constellation size between 4 and 256). This equalizer needs to operate on "complex" signal values and equalization filters. The second system is a VSB system (with porgrammable constellation size between 2 and 8). This equalizer needs to operate on "T/2" signal values and equalization filters. Signal constellations are +/- odd integers derived from "nLevels" in setup code, then normalized to unit energy. Both equalizers need to consist of a feed forward and descision feedback parts. The actualsize of these two arrays should be determined at setup. The equalizer tap adaptation with tap updates governed by variable gains also determined at setup. You need to know the mathematics of tap updates for both feed forward and feedback sections. This is a litmus test to ensure you know enough for the project. (This means you need to supply the math for both complex and T/2 filters.) As an example, the two function calls (for each equalizer types) are: % Initialization Constellation = [login to view URL](nLevels, nFF, nFB, gFF, gFB); % Training SigOut = [login to view URL](SigIn, DesiredOut); % Single Signal Processing SigOut = [login to view URL](SigIn); Please send me your mathematics via PM