A Comparative Study of Soft Computing Methodologies in
... This proof is followed by the study of Narendra and Parthasarathy [3]. In their pioneering work, they have debated how useful artificial neural networks can be for identification and control purposes. Their paper dwells on the realization of an unknown nonlinearity by artificial neural networks. The ...
... This proof is followed by the study of Narendra and Parthasarathy [3]. In their pioneering work, they have debated how useful artificial neural networks can be for identification and control purposes. Their paper dwells on the realization of an unknown nonlinearity by artificial neural networks. The ...
Imitating others by composition of primitive actions: a neuro
... of the view, that is to find a set of action primitives shared by own generation case and observation of demonstrator’s case as segmented from continuous perceptual trajectories even though their trajectory-level appearances are different between the two. Then, an interesting test is to see how the r ...
... of the view, that is to find a set of action primitives shared by own generation case and observation of demonstrator’s case as segmented from continuous perceptual trajectories even though their trajectory-level appearances are different between the two. Then, an interesting test is to see how the r ...
Using Convolutional Neural Networks for Image Recognition
... important. In traditional models for pattern recognition, feature extractors are hand designed. In CNNs, the weights of the convolutional layer being used for feature extraction as well as the fully connected layer being used for classification are determined during the training process. The improve ...
... important. In traditional models for pattern recognition, feature extractors are hand designed. In CNNs, the weights of the convolutional layer being used for feature extraction as well as the fully connected layer being used for classification are determined during the training process. The improve ...
