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Random neural network

Known as: RNN 
The random neural network (RNN) is a mathematical representation of an interconnected network of neurons or cells which exchange spiking signals. It… 
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Related topics

Related topics

8 relations
Action potentialAlgorithmArtificial neural networkLinear-nonlinear-Poisson cascade model

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Improved Tdnns Using Deep Kernels and Frequency Dependent Grid-RNNS
Time delay neural networks (TDNNs) are an effective acoustic model for large vocabulary speech recognition. The strength of the… 
2015
2015
Quaddirectional 2D-Recurrent Neural Networks For Image Labeling
We adopt Convolutional Neural Networks (CNN) to learn discriminative features for local patch classification. We further… 
2015
2015
On speaker adaptation of long short-term memory recurrent neural networks
Long Short-Term Memory (LSTM) is a recurrent neural network (RNN) architecture specializing in modeling long-range temporal… 
Highly Cited
2015
Highly Cited
2015
Time-series modeling with undecimated fully convolutional neural networks
We present a new convolutional neural network-based time-series model. Typical convolutional neural network (CNN) architectures… 
Highly Cited
2014
Highly Cited
2014
Recurrent Neural Networks for Word Alignment Model
This study proposes a word alignment model based on a recurrent neural network (RNN), in which an unlimited alignment history is… 
Highly Cited
2014
Highly Cited
2014
Not All Neural Embeddings are Born Equal
Neural language models learn word representations that capture rich linguistic and conceptual information. Here we investigate… 
2008
2008
Efficient System for Speech Recognition using General Regression Neural Network
— In this paper we present an efficient system for independent speaker speech recognition based on neural network approach. The… 
1999
1999
Automatic structure and parameter training methods for modeling of mechanical systems by recurrent neural networks
1997
1997
Random neural network recognition of shaped objects in strong clutter
Detecting objects in images containing strong clutter is an important issue in a variety of applications such as medical imaging… 
1996
1996
Models of hierarchical respiratory neuron networks
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