This preview shows pages 1–6. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: EE 3120 Chapter 3 Time Domain Analysis of DiscreteTime Signals TimeDomain Analysis of DiscreteTime Systems Two different types of sampling rate alterations: Decimation and Interpolation x [ n ] Original sequence x [ n ] is decimated (sampled) every M = 3 samples creating 1 2 3 4 5 1 2 3 4 5 Decimation : Sampling the samples [ ] [ ] d x n x Mn = [ ] d x n This may be a way to compress the digital signal, requires less data storage. Interpolation : Filling in the gaps, a way to decompress data The original signal x [ n ] can be reproduced in 2 steps: Step 1: Samples of are expanded to their original location (we must know the original decimation rate. [ ] 0, , 2 ,... [ ] 0 otherwise e x n L n L L x n = = Step 2: An interpolation algorithm can be executed to fill in the gaps Obviously this algorithm is poor, but others can be more accurate. Or maybe decimating by 3 is too severe. That is up to the engineer to decide. For our case L = 3 [ ] d x n [ ] d x n EE 3120 Linear Systems Analysis [ ] 1 f n = is a two sided sequence, the discrete counterpart of the constant function [ ] 1 n = Impulse sequence Kronecker delta sequence n n = if i is a fixed integer ; [ ] n i [ ] n shifts to n i = [ ] 1 n i = n i = n i n n Chapter 3 Elementary discretetime signals and their manipulation EE 3120 Linear Systems Analysis [ ] [ ] [ ] i f n f i n i = = Impulse Sequence Could be samples of an analog signal [ 2] 4 f = [ 1] f = [0] 2 f = [1] f = [2] 5 f =  [3] 1 f = [ ] 4 [ 2] 2 [ ] 5 [ 2]...
View
Full
Document
 Fall '08
 ARAVENA

Click to edit the document details