The purpose of this paper is to present the wavelet tools that enable the detection of temporal interactions of concurrent processes. In particular, the determination of interaction coherence of time-varying signals is achieved using a complex continuous wavelet transform. This paper has used electrocardiogram (ECG) and seismocardiogram (SCG) data set to show multiple continuous wavelet analysis techniques based on Morlet wavelet transform. MATLAB Graphical User Interface (GUI), developed in the reported research to assist in quick and simple data analysis, is presented. These software tools can discover the interaction dynamics of time-varying signals, hence they can reveal their correlation in phase and amplitude, as well as their non-linear interconnections. The user-friendly MATLAB GUI enables effective use of the developed software what enables to load two processes under investigation, make choice of the required processing parameters, and then perform the analysis. The software developed is a useful tool for researchers who have a need for investigation of interaction dynamics of concurrent processes.

Cyber-Physical Systems (CPS) require tools that enable development of design methodology that supports analysis and modeling of Interaction Dynamics of Concurrent Processes (IDCP) represented by the measurement data provided by smart acquisition systems. In this paper, are presented some results of the project aiming at the development of algorithms and software tools that could detect short-lived temporal interaction of concurrent processes. The analysis is performed in time-frequency domain using wavelet tools. Some possibilities of such analysis are presented using an example of coherence investigation of concurrent biomedical processes.

Background: Continuous wavelet transform allows to obtain time-frequency representation of a signal and analyze short-lived temporal interaction of concurrent processes. That offers good localization in both time and frequency domain. Scalogram and coscalogram analysis of two signal interaction dynamics gives an indication of the cross-correlation of analyzed signals in both domains.New methods: We have used genetic algorithm with a fitness function based on signals convolution to find time delay between investigated signals. Two methods of cross-correlation are proposed: one that finds single delay for analyzed signals, and one returns a vector of delay values for each of wavelet transform sub-band center frequencies. Algorithms were implemented using MATLAB.Results: We have extracted the data of simultaneously recorded encephalogram and arterial blood pressure and have investigated their interaction dynamics. We found time delay whose value cannot be precisely determined by scalograms and coscalogram inspection. The biomedical signals used come from MIMIC database.Comparison with existing method(s): Cross-correlation of two complex signals is commonly performed using fast Fourier transform. It works well for signals with invariant frequency content. We have determined the time delay between analyzed signals using wavelet scalograms and we have accordingly shifted one of them, aligning associated events. Their coscalogram indicates the cross-correlation of the associated events.Conclusion: Introducing new methods of wavelet transform in cross-correlation analysis has proven to be beneficial to the gain of the information about process interaction. Introduced solutions could be used to reason about causality between processes and gain bigger insight regarding analyzed systems. (C) 2015 Elsevier B.V. All rights reserved.

movements modeling, so that the joint space trajectories, developed for a large number of humanoid robot revolute joints, would replicate movements of humans. In this development, we consider robot velocity and acceleration constraints. B-spline wavelets are used to represent joint space trajectories. However, due to humanoid robot constraints we have to limit the time-frequency domain of our model. In other words, in the spline wavelet representation of our model, we cannot include high frequency wavelet transform details. This results in a loss of integrity of robot trajectory model. We propose to measure model quality by the ratio of the energy included in the trajectory model to the total energy of the unconstraint trajectory. We call this ratio Trajectory Integrity Index (TII). 

The papers in this special section focus on the topics of control and grid integration using wind energy systems.

In this paper, we present a new approach to evaluation of signal integrity that is based on signal energy density as a function of time and frequency, represented by its wavelet scalogram. Using signal integrity ratio and cumulative energy ratio, we illustrate signal integrity analysis with simulated examples, followed by the demonstration of their usefulness through analysis of experimental data of a real audio amplifier. These figures of merit represent the extent to which the integrity of a signal is diminished by the electromagnetic interference effects and/or nonlinear processes.

This paper presents an approach to radio frequency (RF) power control along a power curve specified as a function of load impedance, which varies with time. The control algorithm was developed to control the output of electrosurgical generators but can be used in any other application, where for time-varying loads, some specific power, voltage and cur rent limits have to be met. Such generators may be voltage-controlled or cur rent-controlled. The principle of voltage control was introduced in the previous paper [1].In this paper, we present and compare simulation results of both principles of control. In particular, we discuss their suitability for operation at low sampling frequencies. These control algorithms, developed for an electrosurgical generator, have already been tested with the real hardware and their operation is very close to the simulation results.

This paper presents an approach to radio frequency (RF) power control along a power curve specified as a function of load impedance, which varies with time. The control algorithm was developed to control the output of electrosurgical generators but can be used in any other application, where for time-varying loads, some specific power, voltage and current limits have to be met. The degree to which this requirement is fulfilled, along with good transient responses to time-varying impedance, determines the quality of the RF power delivered.In this paper, we present simulation results of a control algorithm developed for an electrosurgical generator. We discuss only one mode of operation the cut mode. This control algorithm has already been tested with the real hardware and its operation is very close to the simulation results.

During the last years, the power quality (PQ) issues have been a subject of major concern. The constraints that must be fulfilled by the voltage wave supplied by utility companies have become more and more exigent. For this reason, the PQ measurement equipment requires new and computational efficient algorithms. This paper explores the application possibilities of continuous wavelet transform (CWT) to PQ analysis by means of simulation. The signature of different PQ disturbances on the signal scalogram is shown and some figures of merit are proposed in order to evaluate the quality of a given wave.

A substantial increase of photovoltaic (PV) power generators installations has taken place in recent years, due to the increasing efficiency of solar cells as well as the improvements of manufacturing technology of solar panels. These generators are both grid-connected and stand-alone applications. We present an overview of the essential research results. The paper concentrates on the operation and modeling of stand-alone power systems with PV power generators. Systems with PV array-inverter assemblies, operating in the slave-and-master modes, are discussed, and the simulation results obtained using a renewable energy power system modular simulator are presented. These results demonstrate that simulation is an essential step in the system development process and that PV power generators constitute a valuable energy source. They have the ability to balance the energy and supply good power quality. It is demonstrated that when PV array- inverters are operating in the master mode in stand-alone applications, they well perform the task of controlling the voltage and frequency of the power system. The mechanism of switching the master function between the diesel generator and the PV array-inverter assembly in a stand-alone power system is also proposed and analyzed. Finally, some experimental results on a practical system are compared to the simulation results and confirm the usefulness of the proposed approach to the development of renewable energy systems with PV power generators.

It has been demonstrated that modulating the switching frequency of a power converter is a valuable way for reducing the electromagnetic interference (EMI) due to the switching process. Since we are considering a signal whose frequency content varies with time, wavelets are well suited to analyze the performance of such techniques. In this paper, we evaluate the performance of spread spectrum frequency modulation (SSFM) applied to the EMI reduction of a real power converter that uses periodic pattern switching frequency modulation. The performance of the converter under investigation includes the analysis of the switching voltage spectrum (as the main source of EMI) and the output voltage ripple. This evaluation is performed with two coefficients, i.e., maximum energy ratio (MER) and energy dispersion ratio (EDR), which are figures of merit defined in this paper using time-dependent energy density distribution in frequency, obtained from the scalograms of the analyzed signals. Such figures of merit allow comparison in the time-frequency domain of different modulation techniques and the choice of the best solution for each case in terms of reduction of the peak of noise spectrum.

This paper attempts to shed light on many aspects of renewable energy simulation. Since the subject of renewable energy is quite large, this paper limits its scope to electrical generation for grid connected systems.

The paper presents a comparative study of a renewable energy system using simulation data versus the data recorded for its implementation at the Hybrid Power System Test Bed (HPSTB) at the National Wind Technology Center, NREL. The simulation data were obtained from the model realized using RPM-SIM simulator. This study shows that under different conditions the power, voltage, and frequency traces of a simulated system follow closely those recorded. Consequently, it is concluded that the quality of power generated under different conditions can be evaluated using simulation data and that such simulation study can be used to develop the structure and control strategy of renewable energy system to meet power quality requirements.

A method of highly effective biomedical image compression that includes the reconstruction process with a good convergence rate is presented in the paper. It represents an image in the form of its wavelet modulus maxima decomposition. The technique allows the compressed image representation to include only those wavelet transform coefficients that correspond to the wavelet transform modulus maxima that are determined for each resolution level. The proposed approach to analysis of medical images uses the wavelet modulus maxima decomposition to enhance image features that are not visually apparent. The transient behavior of pixel intensities (that corresponds to edges and singular points) is used for image enhancement. The detection of edges is realized by detecting modulus maxima in a two-dimensional dyadic wavelet transform at the proper scale. This approach to image analysis aims at determining structures of the diseased tissue that are represented by the image edges. It is expected that this technique will help with early detection of cancer when routine interpretation of CT scans is inconclusive and biopsy would be required.

This paper explores the effects of wind farm power fluctuations on the power network. A dynamic simulation of a wind farm is performed and the spatial distribution of the wind turbines is considered. In a wind farm, many wind turbines feed power into the power grid at the point of common coupling. The power fluctuation from one turbine may cancel that of another, which effectively rectifies the power fluctuation of the overall wind farm. The effect of power fluctuations is quantified by measuring the flicker and the voltage variation for different case studies. We took a conservative approach to explore a wind farm that consists mainly of stall-controlled wind turbines with fixed frequency induction generators and a specified grid with a known short circuit capacity

The use of wind power generation is increasingly being pursued as a supplement and an alternative to large conventional central power stations. The specification of the power electronics interface is subject to requirements related not only to the renewable energy source itself but also to its effects on power system operation, especially where the intermittent energy source constitutes a significant part of the total system capacity. In this paper, current technology and new trends in power electronics for the integration of wind power generators are presented.