Time series prediction with single multiplicative neuron model
Single neuron models are typical functional replica of the biological neuron that are derived
using their individual and group responses in networks. In recent past, a lot of work in this …
using their individual and group responses in networks. In recent past, a lot of work in this …
Improved back propagation algorithm to avoid local minima in multiplicative neuron model
The back propagation algorithm calculates the weight changes of artificial neural networks,
and a common approach is to use a training algorithm consisting of a learning rate and a …
and a common approach is to use a training algorithm consisting of a learning rate and a …
Classification of gene expression data using spiking wavelet radial basis neural network
B Chandra, KVN Babu - Expert systems with applications, 2014 - Elsevier
The paper discusses how Spiking Wavelet Radial Basis Neural Network can be effectively
used for the classification of gene expression data. A new spiking function has been …
used for the classification of gene expression data. A new spiking function has been …
[PDF][PDF] Levenberg-Marquardt learning algorithm for integrate-and-fire neuron model
In this paper, Levenberg-Marquardt (LM) learning algorithm for a single Integrate-and-Fire
Neuron (IFN) is proposed and tested for various applications in which a neural network …
Neuron (IFN) is proposed and tested for various applications in which a neural network …
Time-series prediction with single integrate-and-fire neuron
In this paper, a learning algorithm for a single integrate-and-fire neuron (IFN) is proposed
and tested for various applications in which a multilayer perceptron neural network is …
and tested for various applications in which a multilayer perceptron neural network is …
Learning with single integrate-and-fire neuron
In this paper, a learning algorithm for a single integrate-and-fire neuron (IFN) is proposed
and tested for various applications in which a multilayer perceptron based neural network is …
and tested for various applications in which a multilayer perceptron based neural network is …
GPU implementation for arabic sign language real time recognition using multi-level multiplicative neural networks
AS Elons - 2014 9th International Conference on Computer …, 2014 - ieeexplore.ieee.org
Sign Language (SL) recognition has been explored for a long time now. Two main aspects
of successful SL recognition systems are required: High recognition accuracy and real-time …
of successful SL recognition systems are required: High recognition accuracy and real-time …
[PDF][PDF] A compact pi network for reducing bit error rate in dispersive FIR channel noise model
K Burse, RN Yadav, SC Shrivastava… - Proc. of WCSET: 2009 …, 2009 - Citeseer
During signal transmission, the combined effect of the transmitter filter, the transmission
medium, and additive white Gaussian noise (AWGN) are included in the channel which …
medium, and additive white Gaussian noise (AWGN) are included in the channel which …
A neural network using single multiplicative spiking neuron for function approximation and classification
In this paper, learning algorithm for a single multiplicative spiking neuron (MSN) is proposed
and tested for various applications where a multilayer perceptron (MLP) neural network is …
and tested for various applications where a multilayer perceptron (MLP) neural network is …
[PDF][PDF] Artificial Neural Network Type Learning with Single Multiplicative Spiking Neuron.
In this paper, learning algorithm for a single multiplicative spiking neuron (MSN) is proposed
and tested for various applications where a multilayer perceptron (MLP) neural network is …
and tested for various applications where a multilayer perceptron (MLP) neural network is …