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function [enc_comp] = cm_dpske(E,M,mapping,sequence); % [enc_comp] = cm_dpske(E,M,mapping,sequence) % CM_DPSKE differentially encodes a sequence. % E is the average energy, M is the number of c

function [enc_comp] = cm_dpske(E,M,mapping,sequence); % [enc_comp] = cm_dpske(E,M,mapping,sequence) % CM_DPSKE differentially encodes a sequence. % E is the average energy, M is the number of c

function [Pe]=bpsk_over_awgn(snr_in_db) E=1; %Normalize energy snr=10^(snr_in_db/10); sgma=E/sqrt(2*snr); %standard deviation of noise Num=4000; % The number of binary data %generation of bi

function [Pe]=bpsk_over_awgn(snr_in_db) E=1; %Normalize energy snr=10^(snr_in_db/10); sgma=E/sqrt(2*snr); %standard deviation of noise Num=4000; % The number of binary data %generation of bi

function [ar,e]=lpcrr2ar(rr); %LPCRR2AR convert autocorrelation coefs to ar coefs [AR,E]=(RR) %E is the residual energy % could test e each time and remove rows when it gets small % Cop

function [enc_comp] = cm_dpske(E,M,mapping,sequence); % [enc_comp] = cm_dpske(E,M,mapping,sequence) % CM_DPSKE differentially encodes a sequence. % E is the average energy, M is the number of c

function [enc_comp] = cm_dpske(E,M,mapping,sequence); % [enc_comp] = cm_dpske(E,M,mapping,sequence) % CM_DPSKE differentially encodes a sequence. % E is the average energy, M is the number of c

function [enc_comp] = cm_dpske(E,M,mapping,sequence); % [enc_comp] = cm_dpske(E,M,mapping,sequence) % CM_DPSKE differentially encodes a sequence. % E is the average energy, M is the number of c

// ENERGY211/CME211 // // vectors.h - header file for Project 2 // #ifndef CLASS_VECTORS // Make sure this isn't included #define CLASS_VECTORS // more than once #include "matrix.h" // This derived

function [ar,e]=lpcrr2ar(rr); %LPCRR2AR convert autocorrelation coefs to ar coefs [AR,E]=(RR) %E is the residual energy % could test e each time and remove rows when it gets small % Cop