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m thornton.m
function [x,U,D] = thornton(xin,Phi,Uin,Din,Gin,Q)
%
% function [x,U,D] = thornton(xin,Phi,Uin,Din,Gin,Q)
%
% M. S. Grewal, L. R. Weill and A. P. Andrews
% Global Positioning Systems, Inertial Na
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html thggnum.html
Requirements of the Numerical Method
In this section we want to consider the connection between the used
discretization scheme and the grid quality criteria we
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m sa_ex7_15b.m
sa% ESPRIT AOA estimation for a M = 4 element array with noise variance = .1
M = 4; % number of array elements
D = 2; % number of signals
sig2 = .1; % noise variance
th1 = -10*pi/180; %
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m sa_fig7_10.m
% Min-Norm AOA estimation for a M = 6 element array with noise variance = .1
figure;
M=6;
D = 2; % number of signals
sig2=.1;
th1=-5*pi/180;
th2=5*pi/180;
a1=[1];
a2=[1];
temp=eye(M);
u
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m sa_ex7_11.m
% MUSIC AOA estimation for a M = 6 element array with noise variance = .1
tic
M=6;
D = 2; % number of signals
sig2=.1;
th1=-5*pi/180;
th2=5*pi/180;
a1=[1];
a2=[1];
for i=2:M
a1=[a1
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m sa_ex7_15.m
% ESPRIT AOA estimation for a M = 4 element array with noise variance = .1
% use time averages instead of expected values by assuming ergodicity of the mean and
% ergodicity of the correlation.
%
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m validate.m
function [cost,nmodel,output] = validate(model, Xtrain, Ytrain, Xtest, Ytest,estfct, trainfct, simfct)
% Validate a trained model on a fixed validation set
%
% >> cost = validate({X,Y,type,gam,sig2}
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m ffbf.m
function cltfm = ffbf(w,g,h,k);
%FFBF Closed-loop frequency response with arbitrary feedback (MIMO).
%
% CLTFM = FFBF(W,G,H,K) calculates the closed loop MVFR matrix.
% CLTFM
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m fmulf.m
function fout=fmulf(w,f1,f2)
%FMULF Multiply two MVFR matrices.
% FMULF(W,F1,F2) returns an MVFR matrix whose
% component matrices = F1m*F2m,
% where F1m and F2m are the compone
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m fpp.m
function phase = fpp(w,f);
%FPP Calculates principal phases.
% FPP(W,F) returns the principal phases (in degrees) of
% F, an MVFR matrix, as a set of column vectors.
% W is th