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in AI and Deep Learning by (50.2k points)

I'm trying to write Hopfield neural network class in Java, but the network doesn't want to recognize patterns. And I can't understand where is the mistake. Network represents with the interconnection matrix w[n][n]. When the network is taught with some standard pattern I change the interconnection matrix with the following method:

private void teaching(int[] pattern) 

{ //teaching for(int i=0; i<n; i++) 

 for(int j=0; j<n; j++) 

 if(i==j) w[i][j]=0; 


 w[i][j] += pattern[i]*pattern[j]; 

 } }

Then I try to recognize the standard patterns in some similar patterns. The process should be stopped when the state of neurons stop changing or when threshold (65535 iterations) is overcome:

private int[] recognition(int[] pattern) { int net=0, s, j=0; int[] previousState = new int[n]; do{ System.arraycopy(pattern, 0, previousState, 0, n); int r = generateRandom(n); for(int i=0; i<n; i++) net+=pattern[i]*w[i][r]; s = signum(net); pattern[r] = s; j++; if(j>iterThreshold) { System.err.println("Threshold overcome."); return pattern; } }while(!Arrays.equals(pattern, previousState)); return pattern; } signum is an activation function: private static int signum(int x) { //activation function if(x>0) return 1; else return -1; }

The recognition process stops only when the threshold is passed. And out pattern doesn't look like a standard pattern. Please help to find the mistake. Thank you in advance.

1 Answer

0 votes
by (108k points)

You have not initialized the net value to “0” inside the do statement in the recognition function:

private int[] recognition(int[] pattern) 

int net=0, s, j=0; 




 for(int i=0; i<n; i++) 





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