These learning objectives are illustrated through detailed descriptions, examples, and exercises. Using LabVIEW to develop virtual instruments (VIs) that implement digital filters and demonstrate their functioning using a graphical display of pre- and postfiltered signals. Implementation of moving average (MA) and autoregressive moving average (ARMA) model-based digital filters and their implementation in LabVIEW.
The concept of a digital filter as counterpart to the analogue filter and built using software.
įrequency response of a low-pass filter using Bode plots, illustrating the response of the filter with varying frequency of the input signal.Īnalogue filters, their analysis, and synthesis using passive components (resistors and capacitors) as well as active components (operational amplifiers).With this in mind, the chapter introduces the reader to the following topics: Digital filters are generally used to postprocess acquired signals and can be used in conjunction with sophisticated digital signal-processing techniques such as Fast Fourier Transform to perform spectral analysis of acquired signals. In particular, analogue filters are often used to deal with the so-called aliasing phenomenon that is common in data acquisition systems. The main use of these signal-processing techniques is in pre- and postprocessing of sensor signals.
In this chapter, both of these topics are discussed and examples using LabVIEW are presented. Analogue and digital filters are used extensively in sensor signal processing.
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