can anyone explain this coding to me? i dont understand it at all? why the need for the function vec and Daubechies filter?

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%% Voice Record %%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %This program records the voice function [norm_voice,h] = Voice_Rec(sample_freq) option = 'n'; option_rec = 'n'; record_len = 1; %Record time length in seconds %sample_freq = 8192; %Sampling frequency in Hertz sample_time = sample_freq * record_len; 'Get ready to record your voice' name = input('Enter the file name you want to save the file with: ','s'); file_name = sprintf('%s.wav',name); option_rec = input('Press y to record: ','s'); if option_rec=='y' while option=='n', input('Press enter when ready to record--> '); record = wavrecord(sample_time, sample_freq); %Records the input through the sound card to the variable with specified sampling frequency input('Press enter to listen the recorded voice--> '); sound(record, sample_freq); option = input('Press y to save or n to record again: ','s'); end wavwrite(record, sample_freq, file_name); %Save the recorded data to a file with the specified file name in .wav format end [voice_read,FS,NBITS]=wavread(file_name); norm_voice = normalize(voice_read); norm_voice = downsmpl(norm_voice, sample_freq); le=32; h=daubcqf(le,'min'); function vec = normalize(vec) temp_vec = vec-mean(vec); sum_temp_vec = sum(temp_vec.*temp_vec); sqrt_temp_vec = sqrt(sum_temp_vec); vec = (1/sqrt_temp_vec)*temp_vec; function sampled = downsmpl(voice, freq) x=freq; y = freq/2; z=1; a=1; sampled=0; while z<freq, sampled(a) = sqrt(abs(voice(z)*voice(z+1))); a=a+1; z = z+2; end sampled = sampled'; function [h_0,h_1] = daubcqf(N,TYPE) % [h_0,h_1] = daubcqf(N,TYPE); % % Function computes the Daubechies' scaling and wavelet filters % (normalized to sqrt(2)). % % Input: % N : Length of filter (must be even) % TYPE : Optional parameter that distinguishes the minimum phase, % maximum phase and mid-phase solutions ('min', 'max', or % 'mid'). If no argument is specified, the minimum phase % solution is used. % % Output: % h_0 : Minimal phase Daubechies' scaling filter % h_1 : Minimal phase Daubechies' wavelet filter % % Example: % N = 4; % TYPE = 'min'; % [h_0,h_1] = daubcqf(N,TYPE) % h_0 = 0.4830 0.8365 0.2241 -0.1294 % h_1 = 0.1294 0.2241 -0.8365 0.4830 % if(nargin < 2), TYPE = 'min'; end; if(rem(N,2) ~= 0), error('No Daubechies filter exists for ODD length'); end; K = N/2; a = 1; p = 1; q = 1; h_0 = [1 1]; for j = 1:K-1, a = -a * 0.25 * (j + K - 1)/j; h_0 = [0 h_0] + [h_0 0]; p = [0 -p] + [p 0]; p = [0 -p] + [p 0]; q = [0 q 0] + a*p; end; q = sort(roots(q)); qt = q(1:K-1); if TYPE=='mid', if rem(K,2)==1, qt = q([1:4:N-2 2:4:N-2]); else qt = q([1 4:4:K-1 5:4:K-1 N-3:-4:K N-4:-4:K]); end; end; h_0 = conv(h_0,real(poly(qt))); h_0 = sqrt(2)*h_0/sum(h_0); %Normalize to sqrt(2); if(TYPE=='max'), h_0 = fliplr(h_0); end; if(abs(sum(h_0 .^ 2))-1 > 1e-4) error('Numerically unstable for this value of "N".'); end; h_1 = rot90(h_0,2); h_1(1:2:N)=-h_1(1:2:N);