Add to ORKGThis paper presents for students instructions to using parallel algorithms, which can be implemented by analogue adaptive circuits employing some neural networks principles for estimation of parameters of signals in power system. Algorithms based on the standard least-squares (LS) criteria is proposed. The problem of estimation is formulated as an optimization problem and solved by using the gradient descent optimization algorithm. The corresponding architectures of analogue neuron-like adaptive processors are also shown
International Journal of Engineering Intelligent Systems for Electrical Engineering and Communicatio...
Abstract — This paper presents combined RLS-Adaline (Recursive Least Square and adaptive linear neur...
The paper presents an adaptive neural network approach for the estimation of harmonic distortions an...
This paper presents for students instructions to using parallel algorithms, which can be implemented...
In many applications, very fast methods are required for estimating and measurement of parameters of...
In many applications, very fast methods are required for estimating and measurement of parameters of...
Fast determination of parameters of the fundamental waveform of voltages and currents is essential f...
An electronic artificial neural network architecture is presented for estimating the parameters of a...
The importance of the electric power quality (PQ) demands new methodologies and measurement tools in...
The paper presents a new approach for the estimation of harmonic components of a power system using ...
In recent papers [4, 5], a new neural adaptive filtering structure has been proposed, based on a Lea...
English In this thesis we are concerned with the hardware implementation of learning algorithms for...
The design of neural network architectures is carried out using methods that optimize a particular o...
The joint time-frequency analysis of power system quantities is a powerful approach to monitor the d...
Harmonic estimation is the foundation of every active noise canceling method in low-voltage power sy...
International Journal of Engineering Intelligent Systems for Electrical Engineering and Communicatio...
Abstract — This paper presents combined RLS-Adaline (Recursive Least Square and adaptive linear neur...
The paper presents an adaptive neural network approach for the estimation of harmonic distortions an...
This paper presents for students instructions to using parallel algorithms, which can be implemented...
In many applications, very fast methods are required for estimating and measurement of parameters of...
In many applications, very fast methods are required for estimating and measurement of parameters of...
Fast determination of parameters of the fundamental waveform of voltages and currents is essential f...
An electronic artificial neural network architecture is presented for estimating the parameters of a...
The importance of the electric power quality (PQ) demands new methodologies and measurement tools in...
The paper presents a new approach for the estimation of harmonic components of a power system using ...
In recent papers [4, 5], a new neural adaptive filtering structure has been proposed, based on a Lea...
English In this thesis we are concerned with the hardware implementation of learning algorithms for...
The design of neural network architectures is carried out using methods that optimize a particular o...
The joint time-frequency analysis of power system quantities is a powerful approach to monitor the d...
Harmonic estimation is the foundation of every active noise canceling method in low-voltage power sy...
International Journal of Engineering Intelligent Systems for Electrical Engineering and Communicatio...
Abstract — This paper presents combined RLS-Adaline (Recursive Least Square and adaptive linear neur...
The paper presents an adaptive neural network approach for the estimation of harmonic distortions an...