recurrent neural networks in the case of the rnn in figure - this is (tthat isthe value of (tis defined in terms of ( )which in turn is defined in terms of ( and so on till ( we will assume that ( is either predefined by the userset to zero or learned as another parameter/weight (learned like wvor bunrolling simply means writing out the equations that describe the rnn in terms of ( in order to do soof coursewe need fix what the length of the sequencewhich is denoted by in this sectionwe will explore unrolling the few different rnns we explored above we will start with unrolling the rnn where the previous hidden state was used for recurrence (demonstrated in figure - laterwe will also explore the same for rnn having recurrence using previous output and finally unrolling rnn with single output figure - illustrates the unrolled rnn corresponding to the rnn in figure - assuming an input sequence of size similarlyfigure - and figure - illustrate the unrolled rnns corresponding to the rnns shown in figure - and figure - respectively figure - unrolling the rnn corresponding to figure -