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Difference between revisions of "Bilateral Trigeminal neuromotor organic symmetry"
Bilateral Trigeminal neuromotor organic symmetry (view source)
Revision as of 16:05, 8 March 2022
, 2 years ago→Going practical
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In our ANN model, a radial basis function (RBF) has been chosen as the activation function <math>f</math>. In the field of mathematical modelling, an artificial neural network that uses RBF as activation function is properly called a 'radial basis function network'. The output of this network is a linear combination of RBF of the inputs and neuron parameters. RBF has many application, and we choose this one because it is specific for function approximation tasks. | In our ANN model, a radial basis function (RBF) has been chosen as the activation function <math>f</math>. In the field of mathematical modelling, an artificial neural network that uses RBF as activation function is properly called a 'radial basis function network'. The output of this network is a linear combination of RBF of the inputs and neuron parameters. RBF has many application, and we choose this one because it is specific for function approximation tasks. | ||
==== | ====Algorithms and network==== | ||
We decided to initialize two layers and define ten neurons in the hidden layer in order to increase the power of our network. We equipped our ANN with the Levenberg-Marquardt (LM) algorithm as training function to be used and trained with the normalized features computed from the EMG of the left muscles. With the LM algorithm, we were able to achieve the rapid execution of the network.<ref name=":6">Kara S, Dirgenali F, Okkesim S (2006) Detection of gastric dysrhythmia using WT and ANN in diabetic gastroparesis patients. Comput Biol Med 36: 276-290.</ref> | We decided to initialize two layers and define ten neurons in the hidden layer in order to increase the power of our network. We equipped our ANN with the Levenberg-Marquardt (LM) algorithm as training function to be used and trained with the normalized features computed from the EMG of the left muscles. With the LM algorithm, we were able to achieve the rapid execution of the network.<ref name=":6">Kara S, Dirgenali F, Okkesim S (2006) Detection of gastric dysrhythmia using WT and ANN in diabetic gastroparesis patients. Comput Biol Med 36: 276-290.</ref> | ||