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PRINCIPLE OF TRAINING ARTIFICIAL NEURAL NETWORKS USING BACKPROPAGATION ALGORITHM
This paper describes learning process of artificial multi-layer neural network using backpropagation algorithm. To illustrate this process the three layer artificial neural network with two inputs, one hidden layer and one output is used....
JA - Elektronika a optoelektronika, elektrotechnika
- 2007 •
- D
Rok uplatnění
D - Stať ve sborníku
Dynamic Backpropagation
The paper introduces the derivation of the gradient based learning rule for adaptaiton of dynamic systems by gradient backpropagation technique. The original matrix form of the derivation of the adaptation rule is introduced for identificati...
BC - Teorie a systémy řízení
- 2009 •
- Jx
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
Backpropagation for interval paterns
BA - Obecná matematika
- 1997 •
- Jx
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
Convergence Optimization of Backpropagation Artificial Neural Network Used for Dichotomous Classification of Intrusion Detection Dataset
of a backpropagation artificial neural network using well know NSL-KDD 1999 dataset, and thus into the backpropagation learning algorithm are performed. Both techniques provide improvement of backpropagation's learning con...
Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
- 2017 •
- Jimp •
- Link
Rok uplatnění
Jimp - Článek v periodiku v databázi Web of Science
Výsledek na webu
Note on adaptation of nets by backpropagation
BA - Obecná matematika
- 1995 •
- X
Rok uplatnění
X - Nezařazeno
Linear separation by backpropagation in neural nets
BA - Obecná matematika
- 1995 •
- X
Rok uplatnění
X - Nezařazeno
Neural Networks in Identification
This paper examines the possibility of using neural networks in the area of continuous identification of parameters of a dynamic system model. It focuses on the two most frequently used methods for network learning, the backpropagation metho...
BC - Teorie a systémy řízení
- 2003 •
- D
Rok uplatnění
D - Stať ve sborníku
Design of Fully Analogue Artificial Neural Network with Learning Based on Backpropagation
A fully analogue implementation of training algorithms would speed up the training of artificial neural networks. A common choice for training the feedforward networks is the backpropagation with stochastic gradient descent. However, the cir...
Electrical and electronic engineering
- 2021 •
- Jimp •
- Link
Rok uplatnění
Jimp - Článek v periodiku v databázi Web of Science
Výsledek na webu
Identification of Dynamic Systems by Neural Network
This work examines the possibility of using neural networks in the area of continuous identification of parameters of a dynamic system model. It focuses on the two most frequently used methods for network learning, the Backpropagation method...
JB - Senzory, čidla, měření a regulace
- 2003 •
- D
Rok uplatnění
D - Stať ve sborníku
MinBackProp – Backpropagating through Minimal Solvers
We present an approach to backpropagating through minimal problem solvers in end-to-end neural network train ing. Traditional methods relying on manually the orem (IFT) to calculate derivatives to backpropagate through the solution ...
Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
- 2024 •
- JSC •
- Link
Rok uplatnění
JSC - Článek v periodiku v databázi SCOPUS
Výsledek na webu
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