One of many videos on digital signal processing. Initial background is needed to discuss the basics of DSP. Here, we talk about the remarkable mathematical relationship and formula known as Euler’s formula. . . . → Read More: Digital Signal Processing (DSP) Tutorial: Euler’s Formula – Part 1
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This is an introduction to digital signal processing. Here, we begin with an background introduction with geometric series and its application to finding the Fourier Transform for discrete-time signals. Note when we talk about discrete-time signals the example given in the video is for aperiodic signals. Signals that are continuous or discrete in the time-domain [...] . . . → Read More: Digital Signal Processing (DSP) Tutorial: Introduction to Geometric Series and the Discrete-Time Fourier Transform In analog or continuous systems the Fourier transform played a key role in analyzing signals and systems. The inverse z transform represents a time-domain sequence of a z transform function. We note that the z transform for digital signals or discrete-time signals is the digital counterpart of the Laplace transform for continuous-time signals. Both the [...] . . . → Read More: z-Transform Tutorial: z-Transform and Inverse z-Transform Examples & Functions We introduce the z-transform bringing polynomials and rational functions to help analyze linear discrete-time systems. The discrete-time convolution (or FIR convolution) is equivalent to polynomial multiplication and algebraic operations in the z transform domain can be translated as combining or decomposing linear time-invariant (LTI) systems. The most common z-transforms are rational functions, that is, the [...] . . . → Read More: Overview and Introduction to the z-Transform (Polynomial & Rational Functions) |
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