The "predict" function in MATLAB predicts the responses of a linear regression model. For example, in this case:
[YTest(:,i),state]=predict(trainedNet,XTest(:,i));
The "predict" function returns the predicted response values of the model "trainedNet" for the points in "XTest(:, i)".
Now, the "predictAndUpdateState" function predicts responses using a trained recurrent neural network and updates the network state. In this case:
[trainedNet,YTest(:,i)]=predictAndUpdateState(trainedNet,XTest(:,i));
The "predictAndUpdateState" function predicts responses for data in "XTest(:, i)" using the trained recurrent neural network "trainedNet" and updates the network state.
Hence, the major difference between these two functions is that "predict" only forecasts the state, while "predictAndUpdateState" both forecasts and refines the state estimate with new data. Use "predict" when you need a forecast without new data, and "predictAndUpdateState" when you want to immediately refine your prediction with a new measurement.
Moreover, "predictAndUpdateState" is not recommended anymore. Instead, use the "predict" function and utilize the state output to update the "State" property of the neural network.
You can refer the following MathWorks documenation for more information:
