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ELEC421 digital signal
创建日期：2024-04-17 15:33:56
标签： ELEC421
digital signal

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ELEC421 Take-home Assignment

 digital signal, correlation, z-transform, and LTI. Marking rules: • For textbook-type problems: The brief solution is provided (together with the assignment). However the students are still required to submit the solutions for all textbook-type problems to get full marks. The purpose is to ‘force’ the students to practice on such textbook problems similar to those in later exams. • 20 points for Matlab problems: 20 = 8+12 Submission rules: • For textbook-type problems: Submit the hard copy of your solutions in-class if you like. • For Matlab problems: Submit your solution file through Canvas (with the file name like ‘ELEC421_studentName_ID_HW1.pdf’). Please organize everything in a single .doc or .pdf file for the Matlab part; make sure to attach the codes in the end; and make sure that the results are calculated using Matlab and figures/tables are not drawn by hands. Textbook Problems: 1. Consider the system in Fig. 1 with h(n)=u(n)+0.6nu(n). Determine the response y(n) of the system when having the input x(n)= d(n+3)+u(n)-u(n-2). 2. For the signals x(n)={1, 4, 1} and y(n)={1, 1, 1}, (a) Determine the autocorrelation sequence of the signal x(n); and (a1) determine the normalized autocorrelation sequence of x(n). (b) Determine the autocorrelation sequence of y(n) and the cross-correlation sequence {rxy(l)}. 3. Determine the z-transform of the following signals. (a) x(n) = {1, 3, 5, 3,1} (b) x(n) = 0.5nu(n) + n u(n) (c) x(n) = u(n) – u(n-2) + 0.25nu(n+1) (d) x(n) = (an sin(w0n) )u(n), with |a|<1 h(n) h(n) z-2 z-1 + x(n ) y(n) 4. Determine the signal x(n) from X(z) (a) Determine the signal x(n) for the z-transform X(z) = log(1-z), |z|<1. (b) Determine all possible signals x(n) if its z-transform X(z) = 1/(1-0.4z-1+0.03z-2). (c) For , determine x(n) if x(n) is left sided. 5. Suppose the input x(n)=u(n), consider the system shown below: Write down the difference equation, and compute the response of the system y(n). 6. Compute the response of a system (a) Suppose the input x(n)=u(n-1)+ n u(n), compute the response of the system y(n) = 0.3 y(n-1) – 0.02 y(n-2) + 2 x(n) + x(n-1). (b) When h(n) = 0.5nu(n), and x(n) = u(n) – u(n-2) + cos(pn/3) u(n). (c ) Consider the filter y(n) = 0.6y(n-1) + b x(n). Determine b so that |H(z)|=1 for z=1. Matlab assignments: 2 problems in total 1. (Digital signal) Consider the following analog sinusoidal signal xa(t)=cos(2p f0 t). (a) Sketch (plot) the signal xa(t) for 0≤t≤20 for f0=1, 1.5, and 4 Hz respectively. (b) For the sample rate Fs = 4Hz, plot the digital signal x(n) for 0≤n≤99. Explain the similarities and differences among the various plots (for f0=1, 1.5, and 4 Hz respectively). (c) Suppose that f0 =5Hz and Fs=20Hz. Plot the signal x(n). What is the frequency of the signal x(n)? (d) Same as in (c), let y(n)=x(2n-1), i.e. by taking the even-numbered samples of x(n), is this a sinusoidal signal? Why? If so, what is its frequency? 21 3 )25.01( 3)( - - - = z zzX 2 2. (Correlation analysis of EEG channels) Figure 1. Bulb-squeezing Task EEG data description: During the experiment, subjects were seated 2 m away from a large computer screen. They were asked to squeeze a pressure responsive bulb with their right hand in order to match vertical target bars on the screen that represented 25 % of maximum voluntary contraction (MVC). The task consisted of 7 squeezing trials, where each trial contained 10 seconds of rest period followed by 2 seconds of squeezing (see Figure 1). EEG signals are sampled at 250 Hz. Please download both ‘pdData.mat’ (the EEG data for a subject with Parkinson’s disease) and ‘normalData.mat’ (the EEG data for a normal subject). Each data file contains three variables: • data (number of channels x number of timepoints) • ampVec (1 x number of timepoints); ampVec(t)=1 during squeezing, amp(t)=0 during rest • channel_name (1xnumber of channels) Sub-problems: (a) Plot the second EEG node, plot the data. (b) Separate the data into the rest part and the squeezing part based on the vector ampVec. (c) Based on the EEG data of the ‘rest’ state, calculate the covariance matrix C_r; Based on the EEG data of the ‘squeezing’ state, calculate the covariance matrix C_s. (d) Based on the EEG data of the ‘rest’ state, calculate the matrix R of correlation coefficients, and comment on the dependencies between the EEG nodes. (You can use ‘mesh’ commend to display the matrix R.) Compare the differences between the Pakinson’s disease subject the normal subject (e.g. based on features such as the eigenvalues of R; For each EEG node k, calculate the summation of R(k,j) over j and use such summations as features for comparison) and comment on your results. (e) Repeat (d) for the ‘squeezing’ state. 


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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 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