Download An Introduction to Wavelet Modulated Inverters by S. A. Saleh PDF

By S. A. Saleh

The introductory bankruptcy in brief provides the elemental topologies and operation of strength inverters. the second one bankruptcy incorporates a description of wavelet foundation capabilities and sampling thought with specific connection with the switching version of inverters. bankruptcy 3 outlines the relationship among the non-uniform sampling theorem and wavelet features to improve a fantastic sampling-reconstruction method to function an inverter for acquiring its optimum performances. the size dependent linearly mixed foundation capabilities are built in bankruptcy 4 so that it will effectively function unmarried part wavelet modulated inverters. bankruptcy 4 additionally includes the advance of the non-dyadic style multiresolution research, which are liable for sampling and recontruction of 3 non-stop time reference modulating indications for 3 part inverters. The performances of unmarried part wavelet modulated inverters for static, dynamic and non-linear lots are offered in bankruptcy 5, whereas bankruptcy six comprises the simulation and experimental performances of 3 part wavelet modulated voltage resource inverters for various quite a bit at a number of working stipulations. This booklet offers the most recent know-how within the advancing energy electronics field.Content:
Chapter 1 creation to energy Inverters (pages 1–17):
Chapter 2 Wavelets and the Sampling Theorem (pages 19–39):
Chapter three Modeling of strength Inverters (pages 41–63):
Chapter four Scale?Based Linearly mixed Wavelets (pages 65–83):
Chapter five Single?Phase Wavelet Modulated Inverters (pages 85–106):
Chapter 6 Three?Phase Wavelet Modulated Inverters (pages 107–129):

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Additional info for An Introduction to Wavelet Modulated Inverters

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6 Two successive interpolating functions λd(t) and λd+1(t) and their normalized associated ON-switched inverter output. 7 Reconstructing sinusoidal signals for the PWM case: (a) reconstructing a sinusoidal signal using the interpolating functions generated by the sampling-based model ({λd(t)}d=1,2…,D) and (b) the reconstructed sinusoidal signal using switching pulses generated by the PWM technique. 08 kHz: (a) the reconstructed sinusoidal signal using {λd(t)}d=1,2…,D, (b) the reconstructed sinusoidal signal using switching pulses generated by the SPWM technique, (c) the spectrum of the reconstructed sinusoidal signal using {λd(t)}d=1,2…,D, and (d) the spectrum of the reconstructed sinusoidal signal using switching pulses generated by the SPWM technique.

Scaling and wavelet basis functions are stable sets of basis functions. Moreover, these basis functions are localized in time and frequency, which makes them capable of spanning complete linear spaces. In general, a set of functions is a basis if it can meet the following conditions. 16) where C is the set of complex numbers. 23) Scaling and wavelet basis functions are special cases of Hilbert space basis functions with capabilities of constructing stable MRAs. The following subsections provide brief descriptions of conventional classes of wavelet basis functions along with main characteristics of their spanned spaces.

2 WAVELET BASIS FUNCTIONS Wavelet Basis functions provide a system of coordinates in which several classes of linear operators are sparse. This system of coordinates is capable of expanding signals at different levels of resolution using coefficients in linear combinations of sets of basis functions. Temporal expansion is performed with contracted and highfrequency bases, while frequency analysis is performed with dilated and lowfrequency ones. In general, wavelet basis functions can expand (decompose) signals and provide a time location for each frequency component present in such decomposed signals.

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