1 / 8

Discrete-Time Signals and Systems

Discrete-Time Signals and Systems. Signals. A function, e.g. sin( t ) in continuous-time or sin(2 p n / 10) in discrete-time, useful in analysis A sequence of numbers, e.g. {1,2,3,2,1} which is a sampled triangle function, useful in simulation

vianca
Télécharger la présentation

Discrete-Time Signals and Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Discrete-Time Signals and Systems

  2. Signals • A function, e.g. sin(t) in continuous-time orsin(2 p n / 10) in discrete-time, useful inanalysis • A sequence of numbers, e.g. {1,2,3,2,1} which is a sampled triangle function, useful insimulation • A collection of properties, e.g.even, causal, and stable, usefulinreasoningabout behavior • A piecewise representation, e.g. • A functional, e.g. d(t)

  3. d[n] n Kronecker Impulse (Function) • Let d[n] be a discrete-time impulse function, a.k.a. the Kronecker delta function: • Impulse response h[n]: response of a discrete-time LTI system to a discrete impulse function 1

  4. x(t) x[n] T{•} T{•} y(t) y[n] Systems • Systems operate on signals to produce new signals or new signal representations • Single-input one-dimensional continuous-time systems are commonly represented in two ways As operators As block diagrams

  5. System Properties • Let x[n], x1[n], and x2[n] be inputs to a linear system and let y[n], y1[n], and y2[n] be their corresponding outputs • A linear system satisfies Additivity: x1[n] + x2[n]  y1[n] + y2[n] Homogeneity: a x[n]  a y[n] for any constant a • Let x[n] be the input to time-invariant system and y[n] be its corresponding output. Then,x[n - m]  y[n - m], for any integer m

  6. s(t) Ts t Ts Sampled analog waveform Sampling • Many signals originate as continuous-time signals, e.g. conventional music or voice • By sampling a continuous-time signal at isolated, equally-spaced points in time, we obtain a sequence of numbers n {…, -2, -1, 0, 1, 2,…} Ts is the sampling period.

  7. Fs = 44.1 kHz Ts = 0.023 ms Fs = 44.1 kHz Ts = 0.023 ms x(t) A/D OpticalDiskWriter OpticalDiskReader D/A x(t) v[n] CD v[n] Recording Studio Stereo System / PC Sampling • Consider audio compact discs (CDs) • Analog-to-digital (A/D) conversion consists of filtering, sampling, and quantization • Digital-to-analog (D/A) conversion consists of interpolation and filtering

  8. n stem plot Generating Discrete-Time Signals • Uniformly sampling a continuous-time signal • Obtain x[n] = x(nTs) for - < n < . • How to choose Ts? • Using a formula • x[n] = n2 – 5n + 3, for n 0would give the samples{3, -1, -3, -3, -1, 3, ...} • We really do not know what the sequence looks like in continuous time because we do not have a sampling period associated with it

More Related