I Sr. No. Topic 1. 2. 3. 4. 5. 6. To perform sampling and explain the concept of aliasing using MATLAB. To perform convolution between two continuous time signals using MATLAB. To perform correlation and autocorrelation using programming in MATLAB. To perform Fourier Series Analysis and Find Fourier coefficients from a complex signal in MATLAB. To plot frequency response of LPF‚ HPF‚ BPF filters in MATLAB. *To design and realize on a breadboard MOD 10 UP/DOWN Counter. 7. *To design and realize
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3D Gradient Vector Flow Matlab Implementation Gradient Vector Flow (to the right) calculated on the volume to the left. Gradient Vector Flow (GVF) is a feature-preserving diffusion of gradient information. It was originally introduced by Xu and Prince to drive snakes‚ or active contours‚ towards edges of interest in image segmentation. But GVF is also used for detection of tubular structures and skeletonization. In this post I present a simple Matlab implementation of GVF for 3D images which
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An Introduction to Matlab Version 2.3 David F. Griffiths Department of Mathematics The University Dundee DD1 4HN With additional material by Ulf Carlsson Department of Vehicle Engineering KTH‚ Stockholm‚ Sweden Copyright c 1996 by David F. Griffiths. Amended October‚ 1997‚ August 2001‚ September 2005. This introduction may be distributed provided that it is not be altered in any way and that its source is properly and completely specified. Contents 1 MATLAB 2 Starting Up 2.1 Windows Systems
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coordinates or coordinates in an arbitrary system. Some other based on old (local) system. With so many geodetic datums in current use‚ it is becoming almost common practice to transform coordinates from one datum to another. For an example‚ a surveyor‚ using GPS‚ will obtain the WGS 84 geocentric‚ geodetic or Cartesian coordinates of the survey point. In order to plot the position on the corresponding local map‚ these WGS 84 coordinates must be first transformed into the local datum on which the map is
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MATLAB BEGINNER’S GUIDE 0 About MATLAB MATLAB is an interactive software which has been used recently in various areas of engineering and scientific applications. It is not a computer language in the normal sense but it does most of the work of a computer language. Writing a computer code is not a straightforward job‚ typically boring and time consuming for beginners. One attractive aspect of MATLAB is that it is relatively easy to learn. It is written on an intuitive basis and it does not
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components – MATLAB – Revision‚ Numerical Integration‚ Root Finding • Dr Mike Clee • Lectures – Weeks 2-4‚ Labs – Weeks 3-5 • 50% 1 assignment – CAD – Solidworks • Dr Chengyuan Wang • Lectures Weeks 5-6‚ Labs – Weeks 6-12 • 50% – 1 assignments Semester 1‚ 2014-2015 General Information • MATLAB lab slots – There will be demonstrators in each lab to help with MATLAB worksheets – Each student has the opportunity to complete the assignment during the lab sessions – Remember - MATLAB labs will be
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Zero Knowledge Authentication Scheme based on Discrete Log Vineeth Pillai Department of Computer Science‚ Illinois Institute of Technology‚ Chicago‚ USA vipillai@hawk.iit.edu‚ CWID: A20260824 April 26‚ 2012 Abstract: This paper details a variant of the parallel version of zero knowledge proof of identity which tries to optimize the space usage and number of iteration by not sacrificing the soundness factor. This protocol could a suitable candidate for smart card based authentication schemes
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The RiskMetrics Group Working Paper Number 99-07 On Default Correlation: A Copula Function Approach David X. Li This draft: April 2000 First draft: September 1999 44 Wall St. New York‚ NY 10005 david.li@riskmetrics.com www.riskmetrics.com On Default Correlation: A Copula Function Approach David X. Li April 2000 Abstract This paper studies the problem of default correlation. We first introduce a random variable called “timeuntil-default” to denote the survival time of each
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Matlab 1.1.7 f(n) = u(n)-n(n-4) n = -5:5; f = (n >= 0); g = (n >= 4); stem (n‚(f-g)) g(n)=r(n)-2r(n-5)+r(n-10) n = -15:15; r = n.*(n >= 0); f = (n-5).*((n-5)>=0); h = (n-10).*((n-10)>=0); g = r - 2.*f + h; stem (n‚g) x(n) = δ(n) - 2δ(n-4) n = -5:5; f = (n == 0); g = ((n-4)==0); x = f - 2.*g stem (n‚x) y(n) = (0.9)^n (u(n)-u(n-20)) n = -20:20; f = (n >= 0); g = ((n-20)>=0); y = 0.9.^n.*(f-g); stem (n‚y) v(n) = cos
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Zoe Hall Often times‚ when an individual with only basic knowledge of biological anthropology considers the adaptation and evolution a group‚ the importance of coevolution is either overlooked or understated. In the article Manipulation complexity in primates coevolved with brain size and terrestriality‚ which can be found in the magazine Nature‚ authors Sandra A. Heldstab‚ Zaida K. Kosonen‚ Sonja E. Koski‚ Judith M. Burkart‚ Carel P. van Schaik & Karin Isler‚ find that there is a plethora of evidence
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