Square root using Sequential Cordic Assignment-2 Submitted to: Dr. Sumam David Dept. of Electronics & Communication Engineering NITK Surathkal Submitted by: Rakshith Sharma 10EC87 Vikas Majjagi 10EC107 Mullapudi Srinivas 10EC99 Algorithm: This is implemented for a range of input values < 0.75 since Xin should be less than 1 for the bit notation we used.Here we use the vectoring Mode of CORIC and its Hyperbolic subcase to calculate Xout=sqrt(xin2 -yin2 ) And yout= 0 Bit notation:
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The Capacitated Arc Routing Problem (CARP) is a representative NP-Hard combinatorial optimization problem (Mourão et al. 2005; Mourgaya et al.‚ 2007; Shang et al. 2014; Han et al. 2004)‚ which has been widely applied in real life‚ such as: the path planning of municipal waste cleanup (Teixeira‚ et al. 2004; Rosa et al. 2002)‚ the path planning of sprinkler (Handa et al. 2006)‚ mail delivery planning (Lu et al.‚ 2006; Araoz et al. 2006)‚ salt spreader path planning (Muyldermans et al.‚ 2002)‚ school
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Example 5: Student work Maths Exploration Newton-Raphson method Rationale- For this project I chose to research and analyse the Newton-Raphson method‚ where calculus is used to approximate roots. I chose this topic because it looked extremely interesting and the idea of using calculus to approximate roots‚ seemed intriguing. The aim of this exploration is to find out how to use the Newton-Raphson method‚ and in what situations this method is used Explanation of the Newton-Raphson method
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Three Automation Types A. Fixed Automation A system in which the sequence of processing (or assembly) operations is fixed by the equipment configuration. The operations in the sequence are usually simple. lt is the integration and coordination of many such operations into one piece of equipment that makes the system complex. Typical features: Suited to high production quantities High initial investment for custom-engineered equipment High production
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ADMS 2200: Intro Marketing! January 29th‚ 2013 Review for Numerical Quiz 1 Formulas: 1. Percentage Change: •Change = (New Value - Old Value) / (Old Value) •Example: Sales grew from $30 billion to $31 billion. •($31 - $30) / $30 = 3.3% Change 2. New Value: •New Value = (Old Value) X (1+Percentage Change / 100) •Example: Sales in 2012 were $320‚000. Expecting sales to grow 18% •($320‚000) X (1.18) = $377‚ 600 3. Old Value: •Old Value = (New Value) / (1+Percentage Change / 100) •Example:
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Numerical Simulation of Marangoni-Driven Boundary Layer Flow Over a Flat Plate with an Imposed Temperature Distribution Abstract: A numerical algorithm is presented for studying Marangoni convection flow over a flat plate with an imposed temperature distribution. Plate temperature varies with x in the following prescribed manner: where A and k are constants. By means of similarity transformation‚ the original nonlinear partial differential equations of flow are transformed to a pair of nonlinear
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2009 SIMULIA Customer Conference 1 3D Numerical Analysis of an ACL Reconstructed Knee M. Chizari‚ B. Wang School of Engineering‚ University of Aberdeen‚ Aberdeen AB24 7QW‚ UK Abstract: Numerical methods applicable to the tibia bone and soft tissue biomechanics of an ACL reconstructed knee are presented in this paper. The aim is to achieve a better understanding of the mechanics of an ACL reconstructed knee. The paper describes the methodology applied in the development of an anatomically
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MATLAB Programs 1. Chapter No. Two Program 2.1 MATLAB m-file for the Bisection Method function sol=bisect(fn‚a‚b‚tol) f a = f eval(f n‚ a); f b = f eval(f n‚ b); if f a∗f b > 0; fprintf(’Endpoints have same sign’) return end while abs (b − a) > tol c = (a + b)/2; f c = f eval(f n‚ c); if f a ∗ f c < 0; b = c; else a = c; end end; sol=(a + b)/2; Program 2.2 MATLAB m-file for the Fixed-Point Method function sol=fixpt(fn‚x0‚tol) old= x0+1; while abs(x0-old) > tol; old=x0; x0 = f eval(f n‚ old);
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PRINTING AND NUMERICAL REGISTERING COMPANY v. SAMPSON [EQUITY] [L R] 19 Eq 462 (1875) SIR G. JESSEL‚ M.R.‚: The buyers were about to form a company to work the invention‚ that means to produce tickets with numbers. That was to be their business. They were to produce and sell a commodity‚ the object of the invention being to produce that commodity more cheaply than had been done before. It was an old commodity‚ an old product‚ but had not been produced in the same manner before. The object
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The Waterloo Mathematics Review 9 Iterative Methods for Computing Eigenvalues and Eigenvectors Maysum Panju University of Waterloo mhpanju@math.uwaterloo.ca Abstract: We examine some numerical iterative methods for computing the eigenvalues and eigenvectors of real matrices. The five methods examined here range from the simple power iteration method to the more complicated QR iteration method. The derivations‚ procedure‚ and advantages of each method are briefly discussed. 1 Introduction
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