Informazioni sul documento
- Università
- Politecnico di Milano
- Corso di laurea
- Biomedical Engineering
- Materia
- Biomedical Signal Processing and Medical Images
- Classificazione
- Appunti · Divisi per argomento
- Formato originale
- Testo
- Testo ricercabile
Divisi per argomento di Biomedical Signal Processing and Medical Images per il corso di Biomedical Engineering presso Politecnico di Milano. Materiale proveniente dall’archivio storico Studwiz e classificato per la consultazione online.
Divisi per argomento di Biomedical Signal Processing and Medical Images per il corso di Biomedical Engineering presso Politecnico di Milano. Materiale proveniente dall’archivio storico Studwiz e classificato per la consultazione online.
Qualità dell’importazione: il testo è stato estratto direttamente dal documento originale.
Passaggi rappresentativi riconosciuti nelle diverse parti del materiale. Il testo completo resta presente nella pagina per la ricerca, mentre l’anteprima compatta rende più semplice la lettura.
SYSTEM THEORY A system is defined by a function T{·} which transforms the input sequence x[n] in the output sequence y[n]. LTI systems Linear Time Invariant systems. Z-Transform The Z-transform converts a discrete-time signal, which is a sequence of real or complex numbers, into a complex frequency-domain representation. Definition Representing the discrete -time signal as the sequence x(n) we obtain: Properties Z-Transform and Laplace Transform The Z-transform can be considered as a discrete-time equivalent of the Laplace transform (s-domain). where 𝑠 =𝜎+ 𝑗𝜔 then 𝑧 = 𝑒𝜎𝑇𝑒𝑗𝜔𝑇 hence |𝑧|= 𝑒𝜎𝑇 ∠𝑧 = 𝜔𝑇 Continuous-time Fourier transform is evaluated on the Laplace s-domain's imaginary line, and it is stable in the left half-plane. Each frequency component of the signal is mapped as a point on the imaginary axes: Discrete-time Fourier transform is evaluated over the unit circle of the z -domain, and it is stable within the unit circle. Each frequency component of the signal is mapped as a point on the unit circle: 𝜔=2𝜋𝑓 → 𝑓=𝜔/2𝜋 and 𝑇 =1/𝑓𝑠 so 𝜔𝑇=2𝜋 𝑓/𝑓𝑆 Linearity 𝑍[𝑎𝑥1(𝑛)+𝑏𝑥2(𝑛)]=𝑎𝑋(𝑧)+𝑏𝑋(𝑧) Time shifting 𝑍[𝑥(𝑛−𝑘)]=𝑧−𝑘𝑋(𝑧) Mult. by exponential 𝑍[𝑎𝑛𝑥(𝑛)]=𝑋( 𝑧 𝑎) Convolution 𝑍[𝑥1(𝑛)⊗𝑥2(𝑛)]=𝑋1(𝑧)𝑋2(𝑧) Differentiation 𝑍[𝑛𝑥(𝑛)]=−𝑧 𝑑𝑋(𝑧) 𝑑𝑧 Complex conjugate 𝑍[𝑥∗(𝑛)]=𝑋∗(𝑧∗) Time reversal 𝑍[𝑥(−𝑛)]=𝑋[𝑧−1] wrt the CONTINUOUS – LAPLACE DOMAIN SIGNAL THEORY Signals are representation of quantitative measurements in function of an independent variable. 1-D SIGNAL defined in time : An ordered sequence of numbers that describes the variations and trends of a quantity in time. ➔ The order of the numbers often determined by the order of measurements (or events) in «time» ➔ time is the axis that identifies the order (= ordering axes) MULTIDIMENSIONAL SIGNALS: Multidimensional sequence of…
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