From the Publisher: 
This is undoubtedly the most accessible book on digital signal processing (DSP) available to the beginner. Using intuitive explanations and well-chosen examples, this book gives you the tools to develop a fundamental understanding of DSP theory. The author covers the essential mathematics by explaining the meaning and significance of the key DSP equations. Comprehensive in scope, and gentle in approach, the book will help you achieve a thorough grasp of the basics and move gradually to more sophisticated DSP concepts and applications.

数字信号处理 = Understanding digital signal processing

Harmonics and waveform distortion is a significant power quality problem in modern power systems with high penetration of Renewable Energy Sources (RES). This problem has attracted more attention in recent decades, owing to the increasing integration of power electronic devices and nonlinear loads into power systems. In this paper, Artificial Intelligence (AI) techniques used in different aspects of analyzing harmonics in electrical power networks are reviewed. The tasks of spectrum analysis and waveform estimation or prediction, harmonic source classification, harmonic source location and estimation, determination of harmonic source contributions, harmonic data clustering, filter-based harmonic elimination, and Distributed Generation (DG) hosting capacity in the context of harmonics are considered. The applications of AI in these tasks have been addressed within the literature and are reviewed in this paper. Different AI techniques applied in the study of harmonics such as artificial neural networks, fuzzy systems, support vector machine and decision tree are reviewed. AI techniques mostly outperformed traditional methods in harmonic analysis, particularly under varying operating condition. However, there is still room for improvement regarding the use of combinations of techniques, ensemble learning, optimal structures, training algorithms and further comprehension. This review provides researchers with an insight into research trends in harmonic analysis and outlines opportunities for further research on this increasingly important topic. 

Review of AI applications in harmonic analysis in power systems

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Analysis Of Periodically Time Varying Systems

Decomposition is an important tool that is used in many differential systems for solving real engineering problems and improving the stability of a system. It involves breaking down of high-order linear systems into lower-order commutative pairs. Commutativity plays an essential role in mathematics, and its applications are extended in physical science and engineering. This paper explicitly expresses all form of necessary and sufficient conditions for decomposition of any kind of fourth-order linear time-varying system as commutative pairs of two second-order systems. Regarding the nonzero initial conditions, additional requirements are derived in order to satisfy the decomposition process. In this paper, explicit method for reducing fourth-order linear time-varying systems (LTVS) into two second-order commutative pairs is derived and solved. The method points out the effect of disturbance and sensitivity on the systems and also highlights the necessary and sufficient conditions for commutativity of the decomposed systems. The results are illustrated by solving some examples.

Realization of a Fourth-Order Linear Time-Varying Differential System with Nonzero Initial Conditions by Cascaded two Second-Order Commutative Pairs

This paper studies commutativity of sixth-order differential systems with zero and nonzero initial conditions (ICs). Given a sixth-order differential system $$A$$
 , we find its commutative pair, that is a new differential system $$B$$
 of order $$m \le 6$$
 ; the obtained result will be used to show the input–output equivalency between the cascaded-connected systems $$AB$$
 and $$BA$$
 . Necessary and sufficient conditions for commutativity of sixth-order continuous-time linear time-varying systems (CTLTVSs) are derived. Based on our findings, we discovered that only a small group of sixth-order CTLTVSs has commutative pairs other than their feedback conjugates obtained by constant feedback and forward path gains. The explicit results obtained in this paper will help to fill the gap on commutativity theory, system behaviors which has significant application to science and play an important role in engineering. This research will also address the problems of sensitivity due to changes in ICs or parameters, and also disturbance as a result of external noise. The results are well verified by examples as well as validated by Matlab Simulink tool and Wolfram Mathematica 11.

Commutativity of Sixth-Order Time-Varying Linear Systems

Time-invariant and time-varying filters versus neural approach applied to DC component estimation in control algorithms of active power filters

The paper is related to the problem of modeling and optimizing power systems supplying, among others, nonlinear loads. A software solution that allows the modeling and simulation of power systems in the frequency domain as well as the sizing and allocation of active power filters has been developed and presented. The basic assumptions for the software development followed by the models of power system components and the optimization assumptions have been described in the paper. On the basis of an example of a low-voltage network, an analysis of the selection of the number and allocation of active power filters was carried out in terms of minimizing losses and investment costs under the assumed conditions for voltage total harmonic distortion (THD) coefficients in the network nodes. The presented examples show that the appropriate software allows for an in-depth analysis of possible solutions and, furthermore, the selection of the optimal one for a specific case, depending on the adopted limitations, expected effects, and investment costs. In addition, a very high computational efficiency of the adopted approach to modeling and simulation has been demonstrated, despite the use of (i) element models for which parameters depend on the operating point (named iterative elements), (ii) active filter models taking into account real harmonics reduction efficiency and power losses, and (iii) a brute force algorithm for optimization.

Software Solution for Modeling, Sizing, and Allocation of Active Power Filters in Distribution Networks

In this article, the model of the first order parametric section linear time varying (LTV) has been described. The parameter of the section under examination is non-periodically variable. These sections are the elementary blocks constituting more complex systems of parametric filters. The method aiming to determinate the impulse response of the LTV section has been presented. The results have been illustrated by an example.

Impulse Responses of Generalized First Order LTV Sections

This paper presents the method of analysis of parametric systems in frequency domain. These systems are also referred to as linear time varying systems (LTV). The article includes a description of an analytical method for determining the frequency response of the first order parametric circuit with non-periodically variable parameters. The results have been illustrated by an example.

https://www.degruyter.com/downloadpdf/j/aee.2015.64.issue-3/aee-2015-0029/aee-2015-0029.xml

Time-frequency responses of generalized first order parametric sections*

This paper presents a model of the first order first order parametric section with non-periodically variable parameter.
Those systems are used as parts of more complex parametric filters. A formula, describing filter response to any signal with finite
average power, has been determined. Obtained results have been illustrated by an example.

/pdf/generalised-transmission-model-of-first-order-parametric-1t5vvthyw0.pdf

Generalised transmission model of first order parametric section

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