Here are my codes, I really need help to tune the two regulation parameters to let re1 and re2 < 0.2, I have tried many many values, but still can’t get the optimal results of re1 and re2. Is there any method to search for proper regulation parameters?

> clc;clear;

`m = 128; n = m; ind_s = floor(m*0.05); ind_c = ind_s; x0 = zeros(n,1); x10_spt = randperm(n); x0(x10_spt(1:ind_c)) = randn(ind_c,1); % cor v0 = zeros(m,1); v0_spt = randperm(m); v0(v0_spt(1:ind_c)) = randn(ind_c,1); % Phi {+1, -1} Measurement Phi = 1/sqrt(m) * randn(m,n); % Noise %z = randn(n,1)*sqrt( sigmaSq ); % y data = real(Phi * x0);`

% data = real(Pauli * vec(x0));

% get the simulation measurement estimate value

N = 200;

p = (1+data)/2; % do a map to {(0,1) & 1}

s0 = rand(numel(data),N);

P = repmat(p,1,N);

s = P > s0; % the event: get +1

s1 = sum(s,2); % Determine how many +1s we got

s2 = s1/N;

edata = 2*s2-1; % map to original

% y = edata + noiseT + z;

y = edata + v0 ;

% m = 448, tau1 = tau2 = 0.05 is ok, re1 = 0.0631,re2 = 0.0622;

% then I change the measurement, hoping to get re = 0.0x`tau1=10; tau2=0.05; % Recovery via CVX cvx_begin quiet variable x(n) ; variable v(m); minimize 0.5*pow_pos(norm(y - Phi * x - v),2) + tau1 * norm(x,1) + tau2 * norm(v,1); cvx_end re1 = norm(x - x0, 2)/ norm(x0, 2); re2 = norm(v - v0, 2)/ norm(v0, 2); re1 re2`