Aug 10, 2016 · The UESMANN network is a simple modulated network which achieves smooth switching between qualitatively different functions in a consistent way, ...
Abstract. A number of types of neural network have been shown to be useful for a wide range of tasks, and can be “trained” in a large number of ways.
UESMANN: A feed-forward network capable of learning multiple functions. A brief introduction to the UESMANN network which is further explored in my thesis.
Data-Driven Learning of Feedforward Neural Networks with Different Activation Functions ... UESMANN: A Feed-Forward Network Capable of Learning Multiple Functions.
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What set of functions can be represented by feed forward networks?
UESMANN: A feed-forward network capable of learning multiple functions. JC Finnis, M Neal. From Animals to Animats 14: 14th International Conference on ...
Aug 2, 2016 · Simplistically, you can consider each layer of a feed-forward network to be a polynomial, which can be solved in sequence to obtain the outputs.
Missing: UESMANN: Capable
UESMANN: A feed-forward network capable of learning multiple functions. In International conference on simulation of adaptive behavior (pp. 101–112). Cham ...
Jun 5, 2015 · Yes you can surely use a single network with multiple outputs. Creating separate network is not required and your approach will in no way reduce the network ...
UESMANN: A Feed-Forward Network Capable of Learning Multiple Functions · Neuro-cognitive organization as a side-effect of the evolution of learning ability.
UESMANN: A Feed-Forward Network Capable of Learning Multiple Functions. SAB 2016: 101-112; 2013. [c1]. view. electronic edition via DOI · unpaywalled version ...