Zvichipiwa ndima idzi, ndiudzei chii anodzokororwa tsinga network, uye sei zvakasiyana kubva convolutional tsinga network.
Context:Anodzokorora tsinga network (RNN) kirasi chakagadzirwa tsinga network apo kwokubatana pakati nodes anogona kusika kutenderera, kubvumira goho kubva dzimwe nodes kukanganisa akazotevera chiyamuro chete nodes. Ikoku kunougonesa kuratidzira mufambiro une simba wenguva. Zvichibva pamasangano etsinga anopfuurira mberi, RNNs dzinogona kushandisa mugariro wadzo womukati (chiyeuchidzo) kuti dzigadzirise nhevedzano dzehurefu hunochinja-chinja hwezvinopinda. Izvi zvinoita kuti dzishandiswe pamabasa akadai sokunyorwa kworuoko kusina kukamurwa, kwakabatana kana kuti kunzwisiswa kwokutaura. Recurrent neural networks theoretically Turing complete uye inogona kumhanyisa mapurogiramu asina kurongwa kuti agadzirise mitsara isina kurongwa yezvinopinda.  Shoko rokuti "recurrent neural network" rinoshandiswa kureva kirasi yenetwork ine mhinduro isingaperi, nepo "convolutional neural network" ichireva kirasi ine mhinduro isingaperi. Makirasi ose ari maviri enetwork anoratidza mufambiro wenguva nenguva. A finite impulse recurrent network is a directed acyclic graph iyo inogona kuvhurwa uye kutsiviwa ne strictly feedforward neural network, nepo infinite impulse recurrent network is a directed cyclic graph iyo isingagone kuvhurwa.  Zvose zviviri zvinoguma zvinokurudzira uye zvisingagumi zvinokurudzira zvinodzokorora zvigadziro zvinogona kuva nemamwe mamiriro akachengetwa, uye kuchengetedza kunogona kunge kuri pasi pekutonga kwakananga nehutano hwemagetsi. Kuchengetedza kunogonawo kutsiviwa neimwe network kana girafu kana iyo inosanganisira kunonoka kwenguva kana ine mitsara yekudzokorora. Nyika dzakadaro dzinodzorwa dzinonzi gated state kana gated memory, uye dziri chikamu chenguva refu pfupi memory network (LSTMs) uye gated recurrent units. Izvi zvinonziwo Feedback Neural Network (FNN).
A recurrent neural network is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes. The term "recurrent neural network" is used to refer to the class of networks with an infinite impulse response, whereas "convolutional neural network" refers to the class of finite impulse response.