Filter Bank for MFCC Piecewise function question

Below is the code I have been writing to try to create a mel triangular filter bank.

I start with 300 to 8000 hz range, convert the frequency to mels, and then mels back into frequency to then get the fft_bin numbers.

    clear all;

    g=[300 8000]; % low freqncy and fs/2 for the highest frequency

    freq2mel=1125*log(1+(g/700)); % creating mel scale from the frequency
                                    % answer  [401.25 2834.99]

    f=linspace(0,2835,12); % if we want 10 filter banks that we use the
                             two endpoints and it will put 10 banks between them

                           % answer is [401.25 622.50 843.75 1065.0 1286.25 1507.50 1728.74 
                                         1949.99 2171.24 2392.49 2613.74 2834.99]

    mel2freq=700*(exp(f/1125)-1); % converting the mel back into frequency

                                   %answer is [300 517.33 781.90 1103.97 1496.04 1973.32 2554.33 
                                                3261.62 4122.63 5170.76 6446.70 8000]

    fft_bins=floor((mel2freq/16000)*512); % creating fft bins

                                     %answer is [9 16 25 35 47 63 81 104 132 165 206 256]

My issue is this. I am stuck after this. I keep seeing the below filter bank piecewise function come up but I do not understand what K is in this function. Is k the array of $ \mid(FFT)\mid ^2 $ numbers from the hamming window? how to get the actual filter with the triangular output with magnitude of 1 to pass the $\mid(FFT)\mid^2$ to get my MFCC's. Can someone please help me out. If this is the case, after I pass the K vector to it, whatever that may be, I take the log of those numbers which there should be 12, and then take the DCT of those 12 numbers. That is what MFCC are?

[Kasa]

if you get mfcc code can you please mail to [e-mail] we are working on speech emotion recognition