The ADAptive LINear Element (ADALINE) neural network uses Least Mean Square (LMS) learning rule. This paper presents a comprehensive comparison of three different variable learning rate (VLR) parameter LMS algorithms, for the generalized ADALINE neural network paradigms. These algorithms are used to adjust the weights of the ADALINE neural network, which are tested under three different applica...

Neurules are a kind of hybrid rules integrating neurocomputing and production rules. Each neurule is represented as an adaline unit. Thus, the corresponding neurule base consists of a number of autonomous adaline units (neurules). Due to this fact, a modular and natural knowledge base is constructed, in contrast to existing connectionist knowledge bases. In this paper, we present a method for g...

In the paper, some problems of the methods that are used to analyze the power quality issues are firstly pointed out. A kind of Artificial Neural Networks, Adaline, and its new algorithm for analysis of power quality are presented. The new algorithm has the advantages of being simply calculated and easily implemented through hardware. The simulating results of voltage quality disturbances detec...

In this paper we introduce the generalized feedforward filter, a new class of adaptive filters that combine attractive properties of Finite Impulse Response (FIR) filters with some of the power of Infinite Impulse Response (IIR) filters. A particular case, the adaptive gamma filter, generalizes Widrow’s adaptive linear combiner (adaline) to an infinite impulse response filter. Yet, the stabilit...

A rigorous mathematical analysis is presented of an adaline-like network operating in continuous time with spatially continuous inputs and outputs. Weights adapt continually, whether or not a training signal is present. It is shown that consistent input-output pairs can be learned perfectly provided every pattern is repeated at least once in every N successive inputs, and the input patterns are...

In this paper, we report some results on hardware and software co-design of an adaptive linear neuron (ADALINE) based control system. A discrete-time Proportional-Integral-Derivative (PID) controller is designed based on the mathematical model of the plant. The parameters of the plant model are identified on-line by an ADALINE neural network. In order to efficiently and economically implement t...

This paper presents a self-tuning filter (STF)-based adaptive linear neuron (ADALINE) reference current generation algorithm to enhance the operation of a three-phase three-level neutral-point diode clamped (NPC) inverter-based shunt active power filter (SAPF) under non-ideal (unbalanced and/or distorted) source voltage conditions. SAPF is an effective and versatile mitigation tool for current ...

Harmonics are undesirable greater frequencies that overlaid on the fundamental sinusoidal waveform resulting in creating a distorted waveform. This distortion forms non-sinusoidal composed of set harmonic frequencies, which is harmful to electrical power supply lines. paper proposes an ADALINE-based algorithm simulated with MATLAB using half-cycle samples. Widrow and Hoff developed ADALINE, sin...

By expanding a function in series form it can be represented to an arbitrary degree of accuracy by taking enough terms. It is therefore possible, in principle, to conduct a linear regression on a new set of variables, transformed by a fixed mapping. This leads to a large computational burden and to the need for an infeasible amount of data from which the coefficients must be estimated and is no...