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Views: 94 Anna Dunenkova

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This video looks at an example of how we can interpolate using cubic splines, both the Natural and clamped boundary conditions are considered. Text Book: Numerical Analysis by Burden, Faires & Burden
Views: 32265 The Math Guy

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Views: 32 Morris Dean

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using the text Burden and Faires "Numerical Analysis" 10 edition we complete part b of problem 1 from chapter 3 section 4. The topic is Hermitian polynomials and their use for approximating function when given data points; x, f(x), f'(x). the music is from musopen and is a number from Sergei Prokofiev and is performed by Vadim Chaimovich.

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Views: 64 Kaye Hess

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Views: 77 Candace Odom

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This video discusses three root-finding algorithms found in Section 2.3 of Burden and Faires' Numerical Analysis, 9th edition.
Views: 9860 Jen-Mei Chang

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Views: 2547 Maniruzzaman-Akash

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Views: 70 Dendih destrian

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Views: 4 Luis Stevens

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Our website: https://goo.gl/R8TrzN?49847

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Views: 15 Mai Fuller

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This video looks at how we can use Lagrange interpolation to approximate functions like we use Taylor's polynomials. The xample used in this video is taken from Numerical Analysis by Burden, Faires & Burden, Cengage learning.
Views: 368 The Math Guy

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Here is an exercise on lagrange polynomial construction using Burden and Faires as our guides from their textbook "Numerical Analysis" 10 edition chapter 3 section 1 problem 1 part b.

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In this video I complete a set of basic questions from "Numerical Analysis" by Burden & Faires. Chapter 1 section 1 on calculus review. This chapter introduces the Intermediate Value Theorem. Music: Mykola Leontovych "carol of the bells" performed by Michael Rondeau downloaded from the website www.musopen.org https://musopen.org/music/2731/mykola-leontovych/carol-of-the-bells/

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Calculus Review on Taylor Polynomials which is the first baby step towards beginning a course in Numerical Analysis. "Numerical Analysis" Burden & Faires. music: "Missa Susanne un Jour" Kyrie by: Orlande de Lassus performed by: Stanislav Ossovskiy downloaded from musopen.org https://musopen.org/music/3718/orlande-de-lassus/missa-susanne-un-jour/

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গ্ণিতে নিউমেরিক্যাল মেথড একটি গুরুত্বপূর্ণ অংশ। আমরা এখানে এই গউস সেন্ট্রাল ইন্টারপলেশন সম্পর্কে ধারণা দেয়ার চেষ্টা করব । আশা করি আপনাদের ভালো লাগবে। Here i tried to give concept about Gaussian forward Interpolation formula... if there is any mistake or suggestion please comment...Thanks some info: In the mathematical field of numerical analysis, interpolation is a method of constructing new data points within the range of a discrete set of known data points. In engineering and science, one often has a number of data points, obtained by sampling or experimentation.... https://en.wikipedia.org/wiki/Interpolation The gaussian interpolation comes under the Central Difference Interpolation Formulae which differs from Newton's Forward interpolation formula formula. https://www.mathworks.com/matlabcentral/fileexchange/42741-gaussian-forward-interpolation-formula Newton's Interpolation Formula: Difference between the forward and the backward formula. I was taught that the forward formula should be used when calculating the value of a point near x0 and the backward one when calculating near xn. However, the interpolation polynomial is unique, so the value should be the same. https://math.stackexchange.com/questions/624894/newtons-interpolation-formula-difference-between-the-forward-and-the-backward আধুনিক জীবনে কম্পিউটারের ভূমিকার কথা আলাদা করে বলার কিছু নেই। মুভি দেখা থেকে শুরু করে গেমস খেলা, গান শোনা, নেট ব্রাউজিং- কী না আমরা কম্পিউটার দিয়ে করি। তো এসএসসি বা এইচএসসি পড়তে পড়তে কারও মাথায় ঢুকে যেতে পারে কম্পিউটার বিজ্ঞান নিয়ে পড়ার ভাবনা।..একদম মেইন মেইন সাবজেক্ট গুলোর কথাই বলা হল উপরে। যে কোন একটি বিষয়ে থিসিসের পাশাপাশি আরও পড়ানো হয় নিউমেরিক্যাল এনালাইসিস, ডাটা বেস, কম্পিউটার আর্কিটেকচার, ইকোনমিক্স, ইংলিশ ইত্যাদি। http://10minuteschool.com/blog/computer-science-01/ u can also read: কম্পিউটার ফান্ডামেন্টাল এন্ড নিউমেরিক্যাল এনালাইসিস - আবুল হোসেন চৌধুরী Numerical Analysis -Richard L. Burden Numerical Methods for Scientists and Engineers -Richard Hamming Numerical Recipes -Saul Teukolsky and William H. Press Introductory Methods of Numerical Analysis - S. S. Sastry Analysis of Numerical Methods -Eugene Isaacson & Herbert Kelle
Views: 687 Virtual Classroom

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Views: 75 R. Austin

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Views: 21 Olya Marchenko

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exercise in taylor polynomial construction using a not too simple function. problem 14 from "numerical analysis" by Burden & Faires chapter 1 section 1. music: "Concerto for Cello and Orchestra" - D minor - I. Prelude. Lento - Allegro maestoso by: Edouard Lalo performed by: European Archive downloaded from www.musopen.org

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A tutorial on how import prices increases consumer surplus and decreases producer surplus, the impact of tariffs and the deadweight loss to society. Like us on: http://www.facebook.com/PartyMoreStudyLess
Views: 181204 Economicsfun

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This video introduces some fundamental concepts in writing computer algorithms and the concept of convergence found in Section 1.3 of Burden and Faires' Numerical Analysis, 9th edition.
Views: 1493 Jen-Mei Chang

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Bisection Method explained with examples in a short time ;) Presenter: Atta Ulhaye
Views: 143913 Abdullah Sagheer

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Views: 407 Dániel Böde

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Numerical Solution of Ordinary Differential Equation (ODE) - 1 Prof Usha Department Of Mathemathics IIT Madras
Views: 3477 Numerical Analysis

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Views: 191 Rosalie Khassanova

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Views: 19 A. Elfata

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My student presentation on Numerical Methods-2014
Views: 8 csecmath

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Learn what is Dupont analysis and understand it more clearly using an example. Check out other videos on my channel: Profitability Ratios - Part 1 - Profit margin ratios https://www.youtube.com/watch?v=t1CsX3J3K2Q Profitability Ratios - Part 2 - Return on Assets https://www.youtube.com/watch?v=Vf0vXCIHHOY Profitability Ratios - Part 3 - Return on Capital Employed https://www.youtube.com/watch?v=JGEpmZ7ewS4 Profitability Ratios - Part 4 - Return on Equity https://www.youtube.com/watch?v=_UhRKVJGeic&t=87s Solvency/Liquidity Ratios - Part 1 - Debt to Equity ratio https://www.youtube.com/watch?v=ZSPDRLzUStc&t=31s
Views: 2152 Finance_World

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Completing a numerical analysis exercise from chapter 3 section 1 part A in the Burden and Faires 10th edition "Numerical Analysis". Chapter 3 is on Interpolation. Music for this video is public domain and found on Musopen.org and this track is "Elijah" by Mendelsshon and it is performed by Matthew Hughes.

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Views: 32 Gallegos

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I chosed this question randomly from the numerical analysis burden 9th edition chapter 3 If you have any question comment it here
Views: 50817 Koushan st

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Dalam video ini dibahas cara mencari persamaan interpolasi Cubic Spline atau (Spline Kubik) yang melalui tiga buah titik. Anda juga bisa menganalogikan pembahasan yang ada disini untuk mencari Cubic Spline yang melalui titik-titik yang lebih dari tiga. Pembahasan yang ada disini merujuk pada materi Cubic spline yang ada dalam buku Numerical Analysis, tulisan dari Richard L. Burden dan J Douglas Faires.
Views: 115 Edumath

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Views: 1161 Matthew Fried

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This video shows how solve algebraically for the effect of a tax on a market as well as the government revenue collected from that tax and the deadweight loss created by the tax. The problem is taken from Principles of Microeconomics, 6th Edition, by N. Gregory Mankiw, and is Ch. 8 problem #11. See the "Practice Problems" playlist for an archive of daily practice problems. For more information and a complete listing of videos and online articles by topic or textbook chapter, see http://www.economistsdoitwithmodels.com/economics-classroom/ For t-shirts and other EDIWM items, see http://www.economistsdoitwithmodels.com/merch/ By Jodi Beggs - Economists Do It With Models http://www.economistsdoitwithmodels.com Facebook: http://www.facebook.com/economistsdoitwithmodels Twitter: http://www.twitter.com/jodiecongirl Tumblr: http://economistsdoitwithmodels.tumblr.com
Views: 6958 jodiecongirl

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Managerial Accounting by Dr. Varadraj Bapat,Department of Management,IIT Bombay.For more details on NPTEL visit http://nptel.ac.in
Views: 1830 nptelhrd

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Description Parametric uncertainty is broadly difficult to quantify. In particular, when those parameters don't fit nice distributions it can be hard to generate reasonable simulations. Polynomial chaos is a somewhat obscure technique that leverages a natural connection between probability distributions and orthogonal polynomial families. This talk will demonstrate the technique and its applications. Abstract There is an intricate link between orthogonal polynomial families and well-known probability distributions. Known as Polynomial Chaos, this technique is largely unknown outside of some engineering fields. Nevertheless, the method allows us to model arbitrary distributions (with finite second moment) using distributions that are more familiar, e.g. the uniform or normal distributions. The polynomial chaos technique shifts the burden of understanding random variables to one of understanding deterministic series coefficients. This method is particularly good for understanding dynamical systems with parametric uncertainty. The Polynomial Chaos expansion allows us to generate Monte Carlo simulations with far fewer simulation runs. In addition, we can use the method to quantify uncertainty in observations even when faced with small sample sizes. This talk will demonstrate the derivation of the technique and include some Python examples of ways it can be used to model systems and understand data in the presence of uncertainty. This will be a highly technical talk, touching on elements of measure-theoretic probability and functional analysis. www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Views: 2271 PyData

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Views: 51 Kaye Hess

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Views: 40 William Smith

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Dalam video ini dibahas cara mencari solusi dari sistem persamaan non linier (tak linier). Metode yang digunakan adalah metode Steepest Descent atau Gradient Descent, metode ini tidak membutuhkan analisis dalam pemilihan nilai awal yang baik karena metode ini mudah konvergen. Karena konvergensinya yang lambat biasanya metode Stepeest descent ini digunakan sebagai langkah awal dalam memilih nilai awal untuk metode Newton. Pembahasan yang ada disini merujuk pada materi Cubic spline yang ada dalam buku Numerical Analysis, tulisan dari Richard L. Burden dan J Douglas Faires.
Views: 219 Edumath

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This is one of many topics on Currents Transformers. In part 1, we'll briefly describe the basic operations of a current transformer. In later topics, we go into more details about CT Accuracy class, CT Sizing, CT Polarity, CT Grounding and other CT topics

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Views: 9 Get shop names

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Professor Peter Sandercock, Personal Chair in Medical Neurology, presents the fourth lecture in the 2014 Medical Detectives series entitled, Unravelling the Mystery of Stroke Disease - The Clue's in the Numbers... Ideas about the causes of stroke have evolved over the centuries from the mystical to the realisation that most strokes are due to a plumbing problem - a blocked or burst artery in the brain. In this lecture Professor Peter Sandercock will begin by describing early attempts to map stroke in the population and then explain how the numerical science of epidemics of infectious diseases in populations was successfully applied to stroke to identify its main causes. Recorded on 6 November 2014 at the University of Edinburgh's Anatomy Lecture Theatre.

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Natural orbit perturbations are responsible for the trajectory divergence from the nominal two-body problem, increasing the requirements for orbit control; whereas, in space situation awareness, they influence the orbit evolution of space debris that could cause hazard to operational spacecraft. However, the dynamics of natural orbit perturbations can be leveraged to significantly reduce extreme high mission cost and create new opportunities for space exploration. Alternatives to high fidelity models of the dynamics to predict the actual orbit evolution are semi-analytical techniques, based on averaging of the disturbing potential function (Brouwer 1959, Deprit 1981), which separate the constant, short-period and long-period effects, thus reducing the computational time for long-term analysis. In an era of unlimited computational resources, when the burden of high-fidelity numerical propagation is not anymore a problem, a recent trend emerged in resorting to semi-analytical propagation techniques for Earth-centred orbits and to apply them to new space engineering problems. In this work semi analytical techniques and Hamiltonian dynamics are used first as a tool for understanding the underlying dynamics of orbit perturbations. Then, an optimiser is proposed that progressively explores the phase space and, through spacecraft propulsion manoeuvres, governs the effect of perturbations to reach the desired orbit. Within the optimisation, the dynamics model is progressively improved so that the final optimal result reflect the actual orbit evolution. Two mission applications are presented: the end-of-life design of the ESA INTEGRAL mission, enhancing the effect of luni-solar perturbation through delta-v manoeuvres and the use of variable geometry solar sail for the end-of-life of nano-satellites in medium earth orbit. In the first case the manoeuvre is computed in the eccentricity-inclination-anomaly-of-perigee map, first introduced by Kozai (1962), in the second case the effect of solar radiation pressure is modulated to achieve a long term grow of the orbit eccentricity.
Views: 79 [email protected]

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This video lesson is from the 2008 AP Microeconomics Exam. This video is designed for students to practice the question to enhance their content knowledge on the theory of consumer choice, and as a resource for teachers to use in their classroom. There is no audio in this video lesson, just a continuous video of the questions and answers. The overall objective is for students to pause the video, answer the questions, and play the video to see if they get the questions correct. This is where teachers can explain why the answer is correct to their students if needed. I hope you find this video lesson helpful. The question tested students’ understanding of marginal utility analysis and price elasticity of demand. Part (a) asked students to define marginal utility. Part (b) asked them to identify the change in consumption necessary to maximize utility given numerical values of marginal utilities and prices for two goods. Part (c) asked students to identify the numerical value of the price elasticity of demand and the burden of a per-unit tax given that elasticity.
Views: 27 Chris Thomas

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PyData Seattle 2015 The Open Source Policy Center maintains a Python package (“Tax Calculator”) that uses Numba to model the federal income tax code for policy analysis. In this talk, we describe the construction of TaxBrain, a web app deployed on Heroku that allows non-programmers to use this package. We discuss the particulars of handling computationally intensive workloads with compiled code on a cloud platform. The Open-Source Policy Center (OSPC) seeks to make policy analysis more transparent, trustworthy, and collaborative by harnessing open-source methods to build cutting-edge economic models. Our first package for release is the Tax Calculator. This Python package encodes current federal tax law and can be used to assess how policy reforms will affect government revenue and the distribution of the tax burden across income groups. In order to make this resource available to a large audience, we have created TaxBrain, a web application that allows users to specify Tax Calculator computations through a browser. The results are displayed in the browser as a number of tables, downloadable as CSV files. In this talk, we discuss the architecture of this web app, and its deployment on the Heroku platform. Tax Brain is a unique combination of web-enabled and traditional “scientific stack” Python code. We discuss our lessons learned, and give advice for those who wish to deploy numerical calculation codes in web-accessible environments.
Views: 554 PyData

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Candidate for NC Supreme Court, June 7, 2016 Election. GPAT TV Broadcast, Greenville, NC 27834
Views: 225 GPAT 23

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View more information on the DOE CSGF Program at http://www.krellinst.org/csgf. Matthew Norman North Carolina State University Immense distributed-memory parallelism requires prioritizing the lowering of communication burden in numerical methods, and yet the explicit time steps must be maximized. Focusing on atmospheric simulation, I propose herein various characteristics-based (CB) integration methods. With fully discrete explicit time stepping, CB methods reduce communication and synchronization while allowing large Courant-Friedrichs-Lewy (CFL) time steps. There will be discussion of theory, GPU implementation and efficiency, results, and future work
Views: 170 Krell Institute

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Views: 133 Johans Ceyna

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400 years back, during the dark medieval period which is waiting for its dawn, in a peasant family of Europe a child is born...! Father dies before its birth. Mother, considers the child as burden and abandons the child. Orphaned baby boy grows with unbearable solitude and constant disease. Luckily with a help of distant uncle, boy got the seat in Cambridge university. This not only changes the course of the boy but is the turning point of the mankind itself. Time passes away.... He becomes a genius of science . He becomes the father , mother and teacher of the whole world. He is the scientist of scientists and teaches the world to see the world... He is ...... none other than the great Issac Newton. The video is a brief portrait of that man. please watch it and share with all the children of the world. Yogarajan, KBA.