novelty-detection-ncm/Agnotron-model/Clustering Network/pcaIter_v6.m

function pcaNet = pcaIter_v6(bigY, ts_idx, pcaNet)

% calc features for T+1 based on output at T
yT = bigY(:, ts_idx-1);
 
cT = pcaNet.bigC(:, ts_idx-1);
% cT = cT - eps; % IDK

if pcaNet.learning == 1
    pcaNet.D = updateD_v2(pcaNet.D, cT);

    pcaNet.W = updateW_v5(pcaNet.W, cT, yT, pcaNet.D, pcaNet.etaW, pcaNet.capW, pcaNet.maxW); 

    pcaNet.M = updateM_v4(pcaNet.M, cT, pcaNet.D, pcaNet.inhibCap, pcaNet.etaM, pcaNet.maxM);
end


% update outputs for T+1
y = bigY(:,ts_idx);

c = updateC_v5(...
    pcaNet.W, pcaNet.M, y, pcaNet.changeThresh);

[maxx, thisCluster] = max(c);

pcaNet.bigC(:, ts_idx) = 0;

if maxx > 0
    pcaNet.clusters = [pcaNet.clusters; thisCluster];
    pcaNet.bigC(thisCluster, ts_idx) = c(thisCluster);
else
    pcaNet.clusters = [pcaNet.clusters; 0];
end



end