how do we determine if the system is linear, time-invariant, causal, and BIBO stable ?

For example for y[n] = max{x[n], x[n-1], x[n-2]} and y[n] = mean{x[n-2], x[n-1], x[n], x[n+1], x[n+2]} and y[n] = median{x[n-2], x[n-1], x[n], x[n+1], x[n+2]}

[Dr.Athar Ravish Khan]

you do refer the code for TV or TIV

clc; close all; k=2;%delay n=0:2+k; x=[10 2 5 zeros(1,k)]; %x(n) subplot(411) stem(n,x) xdelay=[zeros(1,k) x(1:3)]; %x(n-2) subplot(412) stem(n,xdelay) y=x+n.*xdelay; %y(n)=x(n)+n*x(n-2) % delayed output y'(n)=x(n-k)+(n-k)*x(n-k-2) nk=(0:length(n)-1+k)-k; ydelayed=[xdelay zeros(1,k)]+nk.*[zeros(1,k) xdelay] subplot(413) stem(0:length(ydelayed)-1,ydelayed) n1=(0:length(n)-1+k); ydin=[xdelay zeros(1,k)]+n1.*[zeros(1,k) xdelay] % output due to delayed input subplot(414) stem(0:length(ydelayed)-1,ydin)

% system is TV