# Does the SimpleRNN in Keras have a hidden state, or does it just use the output value as the hidden state?

When using tf.keras.layers.SimpleRNN,does this SimpleRNN have a hidden state, or does it just use the output value as the hidden state. That is, does it follow the formulas $$h_t = \tanh(w_h\cdot h_{t-1} + w_x\cdot x_{t-1}+b_h)$$, $$y_t = w_o\cdot h_t + b_o$$? Or is $$h_t=y_t$$?

If the input is of length 5, and I make keras.layers.SimpleRNN(1), why are there only 6 parameters according to the summary. There should be 5 for $$w_x$$, 1 for $$b_h$$, 1 for $$w_h$$, and possibly 2 for output, for a total to 7 or 9.