A Multineuron-Based Routing Algorithm of Tile-Based 2-D Mesh

Algorithm 1

Learning algorithm for the perceptron and its parameters.

1. Initialization of variables weights and bias for simplicity is set to zero.

2. Check the halting condition if not achieved, iterate from steps 3 to 7.

3. Repeat Step 4 to Step 6 to perform the training.

4. Initialize the input units X_i to S_i

5. Calculate the output of the input vector using the relation:

6. If there is an estimated error occurred, then update weights and bias

  If Y is not equal to target t

  w_i(new) = w_i(old) + a_ix_i

  b(new) = b(old) + at

  else

  Copy the old weights and bias to the next iteration

  Finally, test the halting condition

 If there is no update in weights from step 3then terminate

 Else Repeat Step 3