• 5 Pages ldpc_225c
    Ldpc_225c

    School: Berkeley

    Low Density Parity Check Decoder Architecture Engling Yeo yeo@eecs.berkeley.edu Department of Electrical Engineering and Computer Sciences University of California, Berkeley Engling Yeo University of California, Berkeley 1 Lowdensity Parity Chec

  • 28 Pages lec24_06
    Lec24_06

    School: Berkeley

  • 15 Pages lec11_06
    Lec11_06

    School: Berkeley

  • 39 Pages lec26
    Lec26

    School: Berkeley

    Transform Transmitter Image Coding - ,. - Transform T,(k., k2) -"'" 1,(k" k2) Quantization -"- Codeword assignment Receiver Inverse transform I T,(k"k2) Decoder What is exploited: Most of the image energy is concentrated in a small nu

  • 26 Pages lec19
    Lec19

    School: Berkeley

  • 15 Pages lec9
    Lec9

    School: Berkeley

    Fb1,07 e.620

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    Lec8

    School: Berkeley

    Fb1,07 e.420

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    Lec7

    School: Berkeley

    Fb920 e.,07 1 2 3 4 5 6 7 8 9 1 0 1 2 1 3 1 4 1 5 1 7 1 8 1 9 2 0 2 1

  • 19 Pages l1magic
    L1magic

    School: Berkeley

    1 -magic : Recovery of Sparse Signals via Convex Programming Emmanuel Cand`s and Justin Romberg, Caltech e October 2005 1 Seven problems A recent series of papers [38] develops a theory of signal recovery from highly incomplete information. The

  • 39 Pages lec26
    Lec26

    School: Berkeley

    Transform Transmitter Image Coding - ,. - Transform T,(k., k2) -"'" 1,(k" k2) Quantization -"- Codeword assignment Receiver Inverse transform I T,(k"k2) Decoder What is exploited: Most of the image energy is concentrated in a small nu

  • 3 Pages lec15
    Lec15

    School: Berkeley

    N ~ 1\ I j j J , ~. . \ -. -r - b ! ! , f . . - , - o. V i I I \ '3 " '?,. '?' nJ I" .-( j r7 ('\t c:a1 -." - . .; -+- o 4Q. -w . .s ,i -. , <; \ \ 'T ) c:c. .".-.J , '.0 ;) - " .- ~ . 4 ~ ~ ., '. .- ! J i

  • 19 Pages lec10
    Lec10

    School: Berkeley

    7 1 0 1 6 1 7 1 8 1 9

  • 33 Pages lec9
    Lec9

    School: Berkeley

  • 26 Pages lec7a
    Lec7a

    School: Berkeley

  • 20 Pages lec7
    Lec7

    School: Berkeley

  • 6 Pages homework4_probs
    Homework4_probs

    School: Berkeley

  • 6 Pages EE225C_Midterm_sheets
    EE225C_Midterm_sheets

    School: Berkeley

    Adaptive Pilot Detect and Coarse Timing Acquisition Block Timing Recovery Unit for a 1.6 Mbps DSSS Receiver EE225C Project Midterm Report Submitted by Mike Sheets msheets@eecs.berkeley.edu November 6, 2000 Design characteristics Power Delay Area 14

  • 18 Pages lec20_06
    Lec20_06

    School: Berkeley

  • 6 Pages EE225C_Proposal_ammer_sheets
    EE225C_Proposal_ammer_sheets

    School: Berkeley

    Timing Recovery Unit for a 1.6 Mbps DSSS Receiver EE225C Project Proposal Submitted by Josie Ammer and Mike Sheets September 21, 2000 System Components: Adaptive Pilot Detect and Course Timing Acquisition (APD&CTA) Mike Sheets (msheets@eecs.berk

  • 7 Pages OFDM_SVD_dejan
    OFDM_SVD_dejan

    School: Berkeley

    OFDM Receiver Design: Singular Value Decomposition for Channel Estimation Dejan Markovi dejan@eecs.berkeley.edu EE225C Midterm Report 7 November 2000 SVD Block Description Tx Encoding & Modulatio n Channel z'1 z'4 U Rx x' V x y y' U Demod

  • 2 Pages TB_2
    TB_2

    School: Berkeley

    - Test Bench use STD.textio.all; library IEEE; use IEEE.std_logic_1164.all; use IEEE.std_logic_signed.all; use IEEE.std_logic_arith.all; entity TB is end TB; architecture stimulus of TB is component Sub_tr is port( Zr : out std_logic_vect

  • 15 Pages ffc_tutorial
    Ffc_tutorial

    School: Berkeley

    A Tutorial on Using SimulinkTM and XilinxTM System Generator to Build Floating-point and Fixed-point Communication Systems For EE225c, 2003 By Changchun Shi Last Updated: March 10, 2003 Berkeley Wireless Research Center EECS Department, University of

  • 5 Pages midterm_pres
    Midterm_pres

    School: Berkeley

    32-Point Fully Parallel FFT Kevin Camera kcamera@eecs.berkeley.edu FFT Block Description 32-points 15MHz input rate 12b words, 5b coef. Optional truncation and saturation Microarchitectures Pure ripple, no booth Carry-save Booth multipliers

  • 34 Pages Lec16_ofdm
    Lec16_ofdm

    School: Berkeley

    E225C Lecture 16 OFDM Introduction EE225C Multipath can be described in two domains: time and frequency Time domain: Impulse response time time time Impulse response Frequency domain: Frequency response time time time Sinusoidal signal as inpu

  • 44 Pages comsoc
    Comsoc

    School: Berkeley

    IEEE SCV Communications Society Lecture CMOS for Ultra Wideband and 60 GHz Communications Bob Brodersen Dept. of EECS Univ. of Calif. Berkeley http:/bwrc.eecs.berkeley.edu Berkeley Wireless Research Center FCC - Unlicensed Spectra UWB ISM 0 UPCS U

  • 29 Pages final_pres
    Final_pres

    School: Berkeley

    Polyphase Filter Bank Architectures for a Space-based Radar Receiver Kevin Camera (kcamera@eecs.berkeley.edu) Changchun Shi (ccshi@eecs.berkeley.edu) EE225C, Fall 2000 Prof. Borivoje Nikolic Prof. Bob Brodersen Outline Project motivation Existing a

  • 1 Page hw5
    Hw5

    School: Berkeley

    EE 225C VLSI Signal Processing Homework 5 Due on April, 2003 The goal of this problem set will be to implement a single carrier, 20 Mbit/sec QPSK transmitter and receiver that uses a synchronizer to compensate for the channel impairments. A prototype

  • 1 Page Lab8
    Lab8

    School: Berkeley

    University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #8 Image Restoration Overview: Spring 2003 In this assignment, you wi

  • 1 Page Lab7
    Lab7

    School: Berkeley

    University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #7 Image Enhancement Overview: Spring 2003 A problem frequently encou

  • 2 Pages Lab6
    Lab6

    School: Berkeley

    University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #6 2D-FIR filter design J. S. Lim, Two-Dimensional Signal and Image Pro

  • 2 Pages Lab3
    Lab3

    School: Berkeley

    University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Lab Assignment #3 Tomography Overview: Spring 2003 In this assignment, you explo

  • 2 Pages Lab2
    Lab2

    School: Berkeley

    University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Lab Assignment #1 Phase-only image reconstruction Overview: Spring 2003 In this

  • 5 Pages Lecture29
    Lecture29

    School: Berkeley

  • 7 Pages Lecture28
    Lecture28

    School: Berkeley

  • 13 Pages Lecture24
    Lecture24

    School: Berkeley

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    Lecture23

    School: Berkeley

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    Lecture22

    School: Berkeley

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    Lecture21

    School: Berkeley

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    Lecture16

    School: Berkeley

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    Lecture15

    School: Berkeley

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    Lecture14

    School: Berkeley

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    Lecture13

    School: Berkeley

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    Lecture11

    School: Berkeley

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    Lecture10

    School: Berkeley

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    Lecture8

    School: Berkeley

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    Lecture7

    School: Berkeley

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    Lecture6

    School: Berkeley

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    Lecture5

    School: Berkeley

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    Lecture4

    School: Berkeley

  • 12 Pages Lecture2
    Lecture2

    School: Berkeley

  • 7 Pages Lecture1
    Lecture1

    School: Berkeley

  • 2 Pages ps2
    Ps2

    School: Berkeley

    UNIVERSITY OF CALIFORNIA AT BERKELEY PROF. EDWARD A. LEE COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 518 CORY HALL BERKELEY, CALIFORNIA 94720 TEL: (510) 642-0455 FAX: (510) 642-2739 EMAIL: eal@eecs.Berkeley.EDU

  • 22 Pages Lec.7_sfg
    Lec.7_sfg

    School: Berkeley

  • 4 Pages info225a
    Info225a

    School: Berkeley

    EECS 225A Digital Signal Processing Gastpar University of California, Berkeley: Spring 2008 January 7, 2008 Course Information (Preliminary Version) 1 Logistics Michael Gastpar, 265 Cory Hall, gastpar@eecs.berkeley.edu, OH Tue Thu 12:40-1:30 Tues

  • 3 Pages hw5_appendix2
    Hw5_appendix2

    School: Berkeley

    Appendix II (extracted from Peimin Chis MS thesis) Correlator After differential demodulation, the next task is to correlate against the local preamble. This can be mathematically written as q[n] = r[n - i] * p * [i] i =0 N -1 = (rI [n - i] + j r

  • 1 Page 1.30
    1.30

    School: Berkeley

  • 26 Pages lec19
    Lec19

    School: Berkeley

  • 17 Pages lec17
    Lec17

    School: Berkeley

  • 4 Pages info225a
    Info225a

    School: Berkeley

    EECS 225A Digital Signal Processing Gastpar University of California, Berkeley: Spring 2007 January 16, 2007 Course Information (Preliminary Version) 1 Logistics Michael Gastpar, 265 Cory Hall, gastpar@eecs.berkeley.edu, OH Tue Thu 12:40-1:30 Tue

  • 10 Pages hw5_appendix3
    Hw5_appendix3

    School: Berkeley

    Appendix III (extracted from Peimin Chi's MS thesis) CORDIC Due to frequency offset, the maximum correlation value is Ne j2fT when there is no noise, as shown in (2.11). To estimate the frequency offset, we need to estimate the phase of the max corre

  • 1 Page hw2
    Hw2

    School: Berkeley

    EE 225C VLSI Signal Processing Homework 2 Due on March 5, 2003 1. Architectural tradeoffs (a) Calculate the energy efficiency and area efficiency metrics, MOPS/mW and MOPS/mm2 , for the following four chips that appeared in the 2003 ISSCC. (b) Compar

  • 15 Pages Lec16_ofdm
    Lec16_ofdm

    School: Berkeley

    E225C Lecture 16 OFDM Introduction EE225C Introduction to OFDM l Basic idea Using a large number of parallel narrow-band subcarriers instead of a single wide-band carrier to transport information l Advantages Very easy and efficient in dealing

  • 1 Page Lab7
    Lab7

    School: Berkeley

    University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #5 Image Enhancement Overview: Spring 2008 A problem frequently encou

  • 6 Pages EE225C_Proposal_ammer_sheets
    EE225C_Proposal_ammer_sheets

    School: Berkeley

    Timing Recovery Unit for a 1.6 Mbps DSSS Receiver EE225C Project Proposal Submitted by Josie Ammer and Mike Sheets September 21, 2000 System Components: Adaptive Pilot Detect and Course Timing Acquisition (APD&CTA) o Mike Sheets (msheets@eecs.berk

  • 57 Pages Lec25
    Lec25

    School: Berkeley

    1 (Wireless) Networks are more than communications. Part II Prof. Adam Wolisz TUBerlin/Vsiting Scholar UCB EE 225C Spring 2003 Intro . Who: Adam Wolisz Professor of EE&CS at the Technische Universitt Berlin (TUB) Germany Chair of Telecommunic

  • 30 Pages wireless_channels
    Wireless_channels

    School: Berkeley

    Wireless Channels Ada Poon, Bob Brodersen Berkeley Wireless Research Center University of California, Berkeley Earth-Ionospheric Waveguide 3 30 kHz, very low frequency (VLF) Large wavelength (>10 km) Wave cant penetrate to the lowest layer of ionos

  • 5 Pages icd_proposal
    Icd_proposal

    School: Berkeley

    I.ADMINISTRATIVE TITLE: Iterative LDPC-Coded Channel Decoder ABSTRACT: This proposal includes algorithms and implementation of iterative decoders based on a Low Density Parity Check (LDPC) coded partial response channel for high speed applications, a

  • 2 Pages Hmwk05
    Hmwk05

    School: Berkeley

    EECS 225A Spring 2005 Homework 5 Due: February 24. Solutions will be posted on that date and you will self-grade your homework. 1. In the following, Z (k ) = R(k ) + j I (k ) is a zero-mean Gaussian random process (meaning R (k ) and I (k m) are ze

  • 11 Pages lec13_06
    Lec13_06

    School: Berkeley

  • 19 Pages lec7_06
    Lec7_06

    School: Berkeley

  • 17 Pages lec23_06
    Lec23_06

    School: Berkeley

  • 11 Pages lec25_06
    Lec25_06

    School: Berkeley

  • 12 Pages lec18_06
    Lec18_06

    School: Berkeley

  • 11 Pages lec5_06
    Lec5_06

    School: Berkeley

  • 12 Pages Soln-midterm-1
    Soln-midterm-1

    School: Berkeley

    EE 225A Spring 2005 First Midterm Exam: Solutions 1. A function of a complex variable z is analytic in a region if (check one): It is continuous at every point in the region. It is differentiable with respect to z at every point in the region. It

  • 1 Page Hmwk02
    Hmwk02

    School: Berkeley

    EECS 225A Spring 2005 Homework 2 Due: February 3. Solutions will be presented on that date and you will self-grade your homework. Note: In all homework problems you are encouraged to use the numeric and/or symbolic capabilities of Matlab or similar f

  • 2 Pages Hmwk03
    Hmwk03

    School: Berkeley

    EECS 225A Spring 2005 Homework 3 Due: February 10. Solutions will be presented on that date and you will self-grade your homework. Note: In all homework problems you are encouraged to use the numeric and/or symbolic capabilities of Matlab or similar

  • 6 Pages Soln04
    Soln04

    School: Berkeley

    EECS 225A Spring 2005 Homework 4 solutions 1. As shown below, a random variable X is the input to a cascade of two systems with random variable outputs Y1 and Y2 . You are given the joint PDF p X ,Y1 ,Y2 ( x, y1 , y 2 ) and told that it satisfies pY

  • 1 Page Hmwk07
    Hmwk07

    School: Berkeley

    EECS 225A Spring 2005 Homework 7 Due: Date March 10. Solutions will be presented on that date and you will self-grade your homework. Note: In all homework problems you are encouraged to use the numeric and/or symbolic capabilities of Matlab or simila

  • 1 Page Hmwk01
    Hmwk01

    School: Berkeley

    EECS 225A Spring 2005 Homework 1 Due: January 27. Solutions will be presented on that date and you will self-grade your homework. Note: In all homework problems you are encouraged to use the numeric and/or symbolic capabilities of Matlab or similar f

  • 5 Pages Soln05
    Soln05

    School: Berkeley

    EECS 225A Spring 2005 Homework 5 solutions 1. In the following, Z (k ) = R(k ) + j I (k ) is a zero-mean Gaussian random process (meaning R(k ) and I (k m) are zero-mean jointly Gaussian for all k and m ) and wide-sense stationary with autocorrelat

  • 6 Pages Soln03
    Soln03

    School: Berkeley

    EECS 225A Spring 2005 Homework 3 solutions 1. In lecture the unit-sample response of a second-order allpass filter was illustrated. a. This filter has only a single independent parameter, which is the location of one of the two poles. Why? b. Startin

  • 5 Pages Soln02
    Soln02

    School: Berkeley

    EECS 225A Spring 2005 Homework 2 solutions 1. Consider a complex signal {z k ,1 k n} . The goal is to find the best approximation to this signal in terms of a complex exponential with some fixed frequency ; that is, the complex coefficients u and

  • 1 Page Matrix-inversion-lemma
    Matrix-inversion-lemma

    School: Berkeley

    EECS 225A Spring 2005 Matrix inversion lemma David G Messerschmitt Version 1.0, May 4, 2005 When both A and (A uv H ) are invertible (where A is a square matrix and u and v are column vectors), the matrix inversion lemma states that (A uv H ) 1 A

  • 2 Pages Singular-linear-equations
    Singular-linear-equations

    School: Berkeley

    Linear equations: Case of singular square matrix David G Messerschmitt Version 1.1, March 2, 2005 For a set of linear equations Ax = b when A is square but singular, there are two cases: Case I: There are no solutions (so we look for the best approx

  • 11 Pages Soln10
    Soln10

    School: Berkeley

    EECS 225A Spring 2005 Selected book problem solutions Chapters 7, 8, and 9 The following problem solutions should assist you in studying for the second midterm. You should learn more if you give each problem a go before looking at the solution.

  • 3 Pages Soln01
    Soln01

    School: Berkeley

    EECS 225A Spring 2005 Homework 1 1. Choose any two of the identities involving finite summations in Table 2.3 of Hayes. a. Verify those identities numerically for 0 N 1000 using Matlab. b. Verify those identities for all N using (and trusting) the

  • 2 Pages Review
    Review

    School: Berkeley

    EECS 225A Spring 2005 Common themes Complex variables Real functions of a complex variable contains z * , not analytic Stationary points * = 0 z Gradient * = 0 z Linear time-invariant systems Complex exponentials Impulse response, transfer functio

  • 2 Pages Soln08
    Soln08

    School: Berkeley

    EECS 225A Spring 2005 Homework 8 solutions 1. In class we showed that if the transfer function for the n - 1 order lattice filter An-1 ( z ) is minimum phase, and n < 1 then An (z ) is also minimum phase. a. Loosen the assumption and assume that only

  • 5 Pages Soln07
    Soln07

    School: Berkeley

    EECS 225A Spring 2005 Homework 7 solutions 1. You wish to design a least-squares inverse filter that realizes (or if necessary approximates) g (k ) hN (k ) = d (k ) , 0 k < M . However, battery power limitations restrict the value of N (number of F

  • 3 Pages Soln09
    Soln09

    School: Berkeley

    EECS 225A Spring 2005 Homework 9 solutions 1. Given an N N autocorrelation matrix R (N) , you are told that the eigenvalues of this matrix, asymptotically as N , approach the values ( | a |< 1 is real-valued) 1 2n 1 + a 2a cos N 2 , 0 n

  • 18 Pages lec2a
    Lec2a

    School: Berkeley

  • 3 Pages Hayes-errata-to-problems
    Hayes-errata-to-problems

    School: Berkeley

    1 Problem 2.13: The matrix A should be ERRATA in Problems (First Printing) A = ;0 1 1 0 x(n) = A cos(n! + ) Problem 3.8: De ne the process x(n) as follows and, in part (c), let ! be a random variable that is uniformly distributed over the interval

  • 17 Pages lec17
    Lec17

    School: Berkeley

  • 1 Page Lab8
    Lab8

    School: Berkeley

    University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #8 Image Restoration Overview: Spring 2007 In this assignment, you wi

  • 1 Page Lab7
    Lab7

    School: Berkeley

    University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #7 Image Enhancement Overview: Spring 2007 A problem frequently encou

  • 1 Page Hmwk08
    Hmwk08

    School: Berkeley

    EECS 225A Spring 2005 Homework 8 Due: March 31. Solutions will be presented on that date and you will self-grade your homework. 1. In class we showed that if the transfer function for the n 1 order lattice filter An1 ( z ) is minimum phase, and n <

  • 1 Page Hmwk09
    Hmwk09

    School: Berkeley

    EECS 225A Spring 2005 Homework 9 Due: April 7, 2005. Solutions will be presented on that date and you will self-grade your homework. 1. Given an N N autocorrelation matrix R (N) , you are told that the eigenvalues of this matrix, asymptotically as N

  • 1 Page Hmwk06
    Hmwk06

    School: Berkeley

    EECS 225A Spring 2005 Homework 6 Due March 3. Solutions will be presented on that date and you will self-grade your homework. Note: In all homework problems you are encouraged to use the numeric and/or symbolic capabilities of Matlab or similar facil

  • 1 Page Hmwk04
    Hmwk04

    School: Berkeley

    EECS 225A Spring 2005 Homework 4 Due: February 17 1. As shown below, a random variable X is the input to a cascade of two systems with random variable outputs Y1 and Y2 . You are given the joint PDF p X ,Y1 ,Y2 ( x, y1 , y 2 ) and told that it satisf

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