lms.rar_回声_回声消除_回声消除 LMS_回声消除 matlab_回声消除代码

function [input_signal, error_signal, desired_signal, filter_output, impulse, filter_current, mse, db, db_avg]=LMS(filter_size, step_size, input_file, iterations) % Function to perform the LMS algorithm on an input file. % Inputs: Filter order, step size, input wav file, number of iterations. % Outputs: Input signal, error estimation signal (echo cancelled), desired signal (echoed signal), adaptive filter output, real impulse response % Estimation of impulse response, mean sqaure error, attenuation (dB), average attenuation. %Read in the input file input_signal = wavread(input_file); % Create the impulse response for the desired signal impulse=zeros(filter_size,1); for (i=1:5) impulse(((i-1)*filter_size/5)+1)=1/i; end % Convolve the impulse with the input signal to generate the desired signal desired_signal = conv(input_signal, impulse); % initialise adaptive filter impulse and input vector to zero vector of length specified at command line filter_current = zeros(filter_size,1); input_vector = zeros(filter_size, 1); % Loop for number of iterations specified in command line. for i=1:iterations i input_vector(1)=input_signal(i); % insert new sample at beginning of input vector. filter_output(i)=dot(filter_current, input_vector); %Caluculate adaptive filter output error= desired_signal(i)-filter_output(i) % Calculate estimation error filter_current = filter_current + 2*step_size*error*input_vector; % Update filter taps by LMS recursion % Shift values in input vector along. for j=filter_size:-1:2 input_vector(j)=input_vector(j-1); end error_signal(i)=error; % store estimation error cost(i)=error*error; % calculate instantaneous cost square error end % Find moving average of error squared. for i=1:iterations-100 mse(i)=mean(cost(i:i+100)); i end %find moving average of db attenuation (averaged to smooth output). for i=1:iterations-2500 db(i)=- 20*log10(mean(abs(desired_signal(i:i+2500)))��./mean(abs(error_signal(i:i+2500)))); i end %find total average db attenuation db_avg=mean(db);