Revision as of 17:24, 12 October 2010 by Zhao148 (Talk | contribs)


Under construction -Jaemin


Quiz Questions Pool for Week 8


Q1. Find the impulse response of the following LTI systems and draw their block diagram.

(assume that the impulse response is causal and zero when $ n<0 $)

$ {\color{White}ab}\text{a)}{\color{White}abc}y[n] = 0.6 y[n-1] + 0.4 x[n] $

$ {\color{White}ab}\text{b)}{\color{White}abc}y[n] = y[n-1] + 0.25(x[n] - x[n-3]) $


Q2. Suppose that the LTI filter $ h_1 $ satifies the following difference equation between input $ x[n] $ and output $ y[n] $.

$ {\color{White}ab} y[n] = h_1[n]\;\ast\;x[n] = \frac{1}{4} y[n-1] + x[n] $

($ \ast $ implies the convolution)

Then, find the inverse LTI filter $ h_2 $ of $ h_1 $, which satisfies the following relationship for any discrete-time signal $ x[n] $,

(assume that the impulse responses are causal and zero when $ n<0 $)

$ {\color{White}ab} x[n] = h_2[n]\;\ast\;h_1[n]\;\ast\;x[n] $


$ \text{Q3.} $

The following figure shows the flow diagram that results for an N=8 FFT algorithm. The bolded line indicates a path from input sample x[7] to DFT sample X[2].

Week8 Q3 FFT.jpg


a) What is the gain of the path?

b) How many paths exist beginning at x[7] and ending up at X[2]? Does the result apply to a general condition? i.e. How many paths are there between every input sample and output sample?

c) Consider DFT sample X[2]. Following paths displayed in the flow diagram. Prove that every input sample contributes the proper amount to the output DFT sample.

i.e. $ X[2]=\sum_{n=0}^{N-1} x[n]e^{-j(2\pi /N)2n} $


$ \text{Q4.} $


$ \text{Q5.} $


Back to ECE 438 Fall 2010 Lab Wiki Page

Back to ECE 438 Fall 2010

Alumni Liaison

Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

Buyue Zhang