for examplen = 1: nTrainingExamples
           inputVector = inputs(:,examplen);
           HiddenLayerOutput = sigmoid( hiddenWeights * inputVector);
           OutputLayerOutput = sigmoid( outputWeights * HiddenLayerOutput);

           l2_error = OutputLayerOutput - targets(:, examplen);
           l2_delta = learningRates(1, i) .* (OutputLayerOutput .* (1 - OutputLayerOutput)) .* l2_error;

           l1_delta = learningRates(1, i) .* (HiddenLayerOutput .* (1 - HiddenLayerOutput)) .* (outputWeights' * l2_delta);

           outputWeights = outputWeights - (l2_delta*HiddenLayerOutput');
           hiddenWeights = hiddenWeights - (l1_delta*inputVector');
       end