Problem Detail: Dynamical systems are those whose evolution can be described by a rule, evolves with time and is deterministic. In this context can I say that Neural networks have a rule of evolution which is the activation function $f(text{sum of product of weights and features})$ ? Are neural networks
- dynamical systems,
- linear or nonlinear dynamical systems?
Can somebody please shed some light on this?
Asked By : Ria George
Answered By : D.W.
A particular neural network does not evolve with time. Its weights are fixed, so it defines a fixed, deterministic function from the input space to the output space. The weights are typically derived through a training process (e.g., backpropagation). One could imagine building a system that periodically re-applies the training process to generate new weights every so often. Such a system would indeed evolve over time. However, it would be more accurate to call this “a system that includes a neural network as one component of it”. Anyway, at this point we are probably descending into quibbling over terminology, which might not be very productive. This site format is a better fit for objectively answerable questions with some substantive technical content.
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