Add to ORKGThe Random Neural Network (RNN) has received, since its inception in 1989, considerable attention and has been successfully used in a number of applications. In this critical review paper we focus on the feed-forward RNN model and its ability to solve classification problems. In particular, we paid special attention to the RNN literature related with learning algorithms that discover the RNN interconnection weights, suggested other potential algorithms that can be used to find the RNN interconnection weights, and compared the RNN model with other neural-network based and non-neural network based classifier models. In review, the extensive literature review and experimentation with the RNN feed-forward model provided us with the necessary gu...
© 2017 IEEE. Randomized neural network (RNN) is a highly feasible solution in the era of big data be...
Random feature mapping (RFM) is the core operation in the random weight neural network (RWNN). Its q...
Context of the tutorial: the IEEE CIS Summer School on Computational Intelligence and Applications (...
The Random Neural Network (RNN) has received, since its inception in 1989, considerable attention an...
The random neural network (RNN) is a recurrent neural network model inspired by the spiking behaviou...
In big data fields, with increasing computing capability, artificial neural networks have shown grea...
Random Neural Networks (RNNs) area classof Neural Networks (NNs) that can also be seen as a specific...
International audienceRandom Neural Networks (RNNs) are a class of Neural Networks (NNs) that can al...
This letter identifies original independent works in the domain of randomization-based feedforward n...
The Random Neural Network (RNN) is a recurrent neural network in which neurons interact with each ot...
Neural networks are being used in areas of prediction and classification, the areas where statistica...
Randomness has always been present in one or other form in Machine Learning (ML) models. The last fe...
Providing a broad but in-depth introduction to neural network and machine learning in a statistical ...
The random neural network (RNN) is a mathematical model for an ``integrate and fire'' spiking networ...
In this paper, we present, a hardware implementation of a random neural network (RNN) model. The RNN...
© 2017 IEEE. Randomized neural network (RNN) is a highly feasible solution in the era of big data be...
Random feature mapping (RFM) is the core operation in the random weight neural network (RWNN). Its q...
Context of the tutorial: the IEEE CIS Summer School on Computational Intelligence and Applications (...
The Random Neural Network (RNN) has received, since its inception in 1989, considerable attention an...
The random neural network (RNN) is a recurrent neural network model inspired by the spiking behaviou...
In big data fields, with increasing computing capability, artificial neural networks have shown grea...
Random Neural Networks (RNNs) area classof Neural Networks (NNs) that can also be seen as a specific...
International audienceRandom Neural Networks (RNNs) are a class of Neural Networks (NNs) that can al...
This letter identifies original independent works in the domain of randomization-based feedforward n...
The Random Neural Network (RNN) is a recurrent neural network in which neurons interact with each ot...
Neural networks are being used in areas of prediction and classification, the areas where statistica...
Randomness has always been present in one or other form in Machine Learning (ML) models. The last fe...
Providing a broad but in-depth introduction to neural network and machine learning in a statistical ...
The random neural network (RNN) is a mathematical model for an ``integrate and fire'' spiking networ...
In this paper, we present, a hardware implementation of a random neural network (RNN) model. The RNN...
© 2017 IEEE. Randomized neural network (RNN) is a highly feasible solution in the era of big data be...
Random feature mapping (RFM) is the core operation in the random weight neural network (RWNN). Its q...
Context of the tutorial: the IEEE CIS Summer School on Computational Intelligence and Applications (...