the course‚ you will have understood: -Basic signal analysis (mostly continuous-time) -Basic system analysis (also mostly continuous systems) -Time-domain analysis (including convolution) -Laplace Transform and transfer functions -Fourier Series (revision) and Fourier Transform -Sampling Theorem and signal reconstructions -Basic z-transform PLD Autumn 2012 Thursday‚ 27 September 12 Signals and Linear Systems Lecture 1 Slide 3 About the course •Lectures - 15-16 hours over 10 weeks •Problem
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Analog Communication Theory: A Text for EE501 Michael P. Fitz The Ohio State University fitz.7@osu.edu Fall 2001 2 Note to Students. This text is an evolving entity. Please help make an OSU education more valuable by providing me feedback on this work. Small things like catching typos or big things like highlighting sections that are not clear are both important. My goal in teaching communications (and in authoring this text) is to provide students with 1. the required theory‚ 2. an insight
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fendpaper.qxd 11/4/10 12:05 PM Page 2 Systems of Units. Some Important Conversion Factors The most important systems of units are shown in the table below. The mks system is also known as the International System of Units (abbreviated SI )‚ and the abbreviations sec (instead of s)‚ gm (instead of g)‚ and nt (instead of N) are also used. System of units Length Mass Time Force cgs system centimeter (cm) gram (g) second (s) dyne mks system meter (m) kilogram (kg) second (s) newton
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the abstract of the document here. The abstract is typically a short summary of the contents of the document.] | Section 2: The following code was used to calculate perform the DFT Function in Matlab: function sw = dft(st) % DFT - Discrete Fourier Transform M = length(st); N = M; WN = exp(2*pi*j/N); %Main Loop for n=0:N-1 temp = 0; for m=0:M-1 s = st(m+1); temp = temp + (s* (WN ^ (-n*m))); end sw(n+1) = temp;
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Recently due to internet growth‚ lots of medical digital images are being shared between medical experts and hospitals for better and more precise diagnosis‚as well as for research and educational purpose and also for many other commercial and non-commercial applications. In modern times now‚ all the integrated health care systems like Hospital Information System (HIS) and Picture Archiving and Communication System (PACS) allow easy distribution of medical imageswherethe whole or the region of interest(ROI)
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The Discrete Cosine Transform (DCT): Theory and Application 1 Syed Ali Khayam Department of Electrical & Computer Engineering Michigan State University March 10th 2003 1 This document is intended to be tutorial in nature. No prior knowledge of image processing concepts is assumed. Interested readers should follow the references for advanced material on DCT. ECE 802 – 602: Information Theory and Coding Seminar 1 – The Discrete Cosine Transform: Theory and Application 1. Introduction
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Q-A. Find the Laplace transform of the following functions 1. f (t) = t − 1‚ 0 < t < 3; 7‚ t > 3. 2. f (t) = cos t − 0‚ 2π 3 ‚ 0 2π . 3 2π ; 3 4‚ 0 < t < 1; −2‚ 1 < t < 3; 3. f (t) = 5‚ t > 3. 5. f (t) = 3t3 + e−2t + t 3 7. f (t) = cos3 2t 9. f (t) = sin (3t + 5) 11. f (t) = e−3t sin2 t 13. f (t) = 7T 15. f (t) = e−3t (cos (4t) + 3 sin (4t)) 17. f (t) = teat 19. f (t) = t sin2 3t 21. f (t) = t2 e−2t cos t 23. f (t) = t cos (7t + 9) 25. f (t) = 27. f (t) = sin2 t t e−t sin t t 1 2
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Abstract: In 1965‚ Cooley and Turkey were two persons who discussed the FFT (Fast Fourier Transform) for the first time in history. In past years‚ researchers believed that a discrete Fourier transform can also be calculated and classified as FFT by using the Danielson-Lanczos lemma theorem. By using this theorem‚ this process is slower than other‚ as it is slightly tainted in speed due to the power of N (exponent of N) are not 2. Therefore‚ if the number of points i.e. N is not a power of two‚
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Jiawei Huang 37154135 Fourier Transform Assignment 1. Fourier transform of sine wave (code): import numpy as np import matplotlib.pyplot as plt from scipy.fftpack import fft‚fftfreq dt = 0.01 time = np.arange(0‚5.‚dt) f_1 = 3. a_1 = 2.3 y = a_1*np.sin(2.*np.pi*time*f_1) plt.plot(time‚y) plt.xlabel("Time t [s]") plt.ylabel("Wave") plt.title("Wave Signal") plt.show() n = time.shape[-1] transform = (fft(y)[:n/2]) * 2./n frequency = fftfreq(n‚time[1]-time[0])[:n/2]
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8051 TUTORIAL Donal Heffernan University of Limerick May-2002 8051 Tutorial D.Heffernan © 2000‚ 2001 1 Blank 8051 Tutorial D.Heffernan © 2000‚ 2001 2 Some reference material: Test books + MacKenzie Scott. The 8051 Microcontroller‚ Prentice Hall. 3rd. Ed.‚ 1999 + Yeralan and Ahluwalia. Programming and Interfacing the 8051 Microcontroller. Addison-Wesley. 1995. U.L. Server (Shared folder) Go to ‘Network Neighborhood’‚ then ‘Entire Network’‚ then pick Domain ‘Intel_Data_Comm’
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