Abstract: A method of construction of a feedforward neural network includes a step of initialization of a neural network according to an initial topology, and at least one topological optimization phase, of which each phase includes: an additive phase including a modification of the network topology by adding at least one node and/or a connection link between the input of a node of a layer and the output of a node of any one of the preceding layers, and/or a subtractive phase including a modification of the network topology by removing at least one node and/or a connection link between two layers. Each topology modification includes the selection of a topology modification among several candidate modifications, based on an estimation of the variation in the network error between the previous topology and each topology modified according to a candidate modification.

Abstract: A method for building a neural network configured to be run on a destination computing unit is implemented by a system including a computer and a memory storing a learning dataset. The method includes providing a neural network having an initial topology, and training the initial topology over the learning dataset. The topology of the neural network is optimized, which includes at least one iteration of the following steps: for each of a plurality of candidate topological changes, estimating the variation induced by the candidate topological change on: the neural network's error, and a value of at least one physical quantity needed for executing the neural network on the destination processing unit, selecting at least one of the candidate topological changes based on said estimation and updating the topology of the neural network according to said selected topological change, and training the updated neural network over the learning dataset.

Abstract: A method of construction of a feedforward neural network includes a step of initialization of a neural network according to an initial topology, and at least one topological optimization phase, of which each phase includes: an additive phase including a modification of the network topology by adding at least one node and/or a connection link between the input of a node of a layer and the output of a node of any one of the preceding layers, and/or a subtractive phase including a modification of the network topology by removing at least one node and/or a connection link between two layers. Each topology modification includes the selection of a topology modification among several candidate modifications, based on an estimation of the variation in the network error between the previous topology and each topology modified according to a candidate modification.