This paper presents issues related to the adaptive control of the drive system with an elastic
clutch connecting the main motor and the load machine. Firstly, the problems and the main …

The creation of multiple applications with a higher level of complexity has been made
possible by the usage of artificial neural networks (ANNs). In this research, an efficient …

Different types of noise contaminating the surface electromyogram (EMG) signal may
degrade the recognition performance. For noise removal, the type of noise has to first be …

Cardiovascular diseases are identified as one of the most dangerous diseases and the
major causes of the death around the world. One of the most common cardiac arrhythmias …

This paper deals with the problem of reference signal generation for Shunt Active Power
Filter (SAPF) capable of reducing the Total Harmonic Distortion (THD) in power system …

The paper studies time series prediction using artificial neural networks. The special
attention is paid to the influence of size of the input vector length. Furthermore, the prediction …

Electromyography (EMG) is a procedure for assessing and recording the electrical activity
produced by skeletal muscles. Since the contracting skeletal muscles are greatly …

The paper presents two derivatives of the Least Mean Square (LMS) algorithm, which can
be utilized in real-time processing of the electrocardiographic (ECG) signals:(i) the …

Muscle-computer interfaces (MCIs) based on surface electromyography (EMG) pattern
recognition have been developed based on two consecutive components: feature extraction …

Accurate estimation of power signal frequency is an important requirement for many
application areas that include system protection, energy quality monitoring and …