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Cortex-M 的代码
exm3.m
[FileName,PathName,FilterIndex]=uigetfile( ...
{ '*.m', 'M-files (*.m)'; ...
'*.fig','Figures (*.fig)'; ...
'*.mat','MAT-files (*.mat)'; ...
'*.mdl','Models (*.mdl)'; ...
'*.*', '
q.m
% File: q.m
% Software given here is to accompany the textbook: W.H. Tranter,
% K.S. Shanmugan, T.S. Rappaport, and K.S. Kosbar, Principles of
% Communication Systems Simulation with Wireless App
matrix_t_pdf.m
function p = matrix_T_pdf(A, M, V, K, n)
% MATRIX_T_PDF Evaluate the density of a matrix under a Matrix-T distribution
% p = matrix_T_pdf(A, M, V, K, n)
% See "Bayesian Linear Regression", T. Min
q.m
% File: q.m
% Software given here is to accompany the textbook: W.H. Tranter,
% K.S. Shanmugan, T.S. Rappaport, and K.S. Kosbar, Principles of
% Communication Systems Simulation with Wireless App
ml_cp.m
function yy=ML_cp()
%%%Algorithm Based：J.-J. Van de Beek, M. Sandell, M. Isaksson, and P. O. B??rjesson,
%%%“ML estimation of time and frequency offset in OFDM systems,” IEEE Trans. Signal Proc.,
mlandcpp.m
function yy=ML_cp()
%%%Algorithm Based：J.-J. Van de Beek, M. Sandell, M. Isaksson, and P. O. B??rjesson,
%%%“ML estimation of time and frequency offset in OFDM systems,” IEEE Trans. Signal Proc.,
xinyuanshumu_page42.m
clc;
clear ;
close all;
tic
M=16;%阵列的天线数
N=3;%信源数
snap=1000;%快拍数目
L=snap;
C=3e8;
lamda=0.2;
f0=C/lamda;
d=0.5*lamda;
% k=d/lamda;
theta0=5;
theta1=20;
theta2=40;
fs=1000;
ts=1/fs;
t=
rx_est.m
function [Rx]=Rx_est(X,M)
% [Rx]=Rx_est(X,M)
% RX_EST Estimates the autocorrelation of the sequence of random
% variables given in X. Only Rx(0), Rx(1), ... , Rx(M) are computed.
% Note
fftseq.m
function [M,m,df]=fftseq(m,ts,df)
% [M,m,df]=fftseq(m,ts,df)
% [M,m,df]=fftseq(m,ts)
%FFTSEQ Generates M, the FFT of the sequence m.
% The sequence is zero padded to meet the required frequen
fftseq.m
function [M,m,df]=fftseq(m,ts,df)
% [M,m,df]=fftseq(m,ts,df)
% [M,m,df]=fftseq(m,ts)
%FFTSEQ Generates M, the FFT of the sequence m.
% The sequence is zero padded to meet the required frequen