101. Ingenta: All Issues -- Journal Of Differential Equations user name. password. remember me. enter. Athens click here to login via Athens. Journal of differential equations, ISSN 00220396 in our http://www.ingenta.com/journals/browse/ap/de

guest need help? online articles fax/ariel articles user name password remember me Athens click here to login via Athens Journal of Differential Equations ISSN 0022-0396 in our archives: Volume 124 (1996) through Volume 187 (2003) Publisher: Academic Press see publisher's website see journal home page LATEST NEXT PREVIOUS EARLIEST Volume 187, Issue 1, January 2003 Volume 186, Issue 2, December 2002 Volume 186, Issue 1, November 2002 Volume 185, Issue 2, November 2002 Volume 185, Issue 1, October 2002 Volume 184, Issue 2, September 2002 Volume 184, Issue 1, September 2002 Volume 183, Issue 2, August 2002 Volume 183, Issue 1, July 2002 Volume 182, Issue 2, July 2002 Volume 182, Issue 1, June 2002 Volume 181, Issue 2, May 2002 Volume 181, Issue 1, May 2002 Volume 180, Issue 2, April 2002

102. Computer Methods For Mathematical Computations Code from the book, translated to ELF, a Fortran 90 subset. Algorithms for calculations in science and engineering, including linear equations, spline interpolation, integration, differential equations, zero finding, minimization and singular value decomposition. http://www.pdas.com/fmm.htm

PDAS home Public Domain Aeronautical Software (PDAS) Computer Methods for Mathematical Computations Computer Methods for Mathematical Computations by George Forsythe, Michael Malcolm and Cleve Moler is one of the great classic textbooks of numerical methods for scientists and engineers. Many people (myself included) have used the book as a reference and used the programs as tools for a variety of computing projects. Although the algorithms are still usable in their original pre-Fortran 77 format, the readability and usability is greatly enhanced by using the coding style of modern Fortran. I have rewritten the procedures in modern Fortran. In particular, the library will now compile correctly using Lahey Essential Fortran (ELF), which is a subset of the general Fortran language. Successful compilation with ELF is a virtual guarantee that you are not using any proprietary Fortran extensions that might affect the portability of your code. List of Procedures and arguments Source code for the library of algorithms Source code for the sample problems Expected results from running the samples Comments on the modern coding These codes are on the current (version 8) disc. I intend to replace the routines that were originally included with some of the aeronautical programs with the counterparts from this library.

103. Ingenta: All Issues -- Differential Equations differential equations, ISSN 00122661 in our archives Volume 36 (2000) through Volume 39 (2003) Publisher MAIK, LATEST NEXT, PREVIOUS forward EARLIEST last. http://www.ingenta.com/journals/browse/klu/dieq

guest need help? online articles fax/ariel articles user name password remember me Athens click here to login via Athens Differential Equations ISSN 0012-2661 in our archives: Volume 36 (2000) through Volume 40 (2004) Publisher: MAIK LATEST NEXT PREVIOUS EARLIEST Volume 40, Issue 1, January 2004 Volume 39, Issue 12, December 2003 Volume 39, Issue 11, November 2003 Volume 39, Issue 10, October 2003 Volume 39, Issue 9, September 2003 Volume 39, Issue 8, August 2003 Volume 39, Issue 7, July 2003 Volume 39, Issue 6, June 2003 Volume 39, Issue 5, May 2003 Volume 39, Issue 4, April 2003 Volume 39, Issue 3, March 2003 Volume 39, Issue 2, February 2003 Volume 39, Issue 1, January 2003 LATEST NEXT PREVIOUS EARLIEST Publisher: MAIK terms and conditions

104. EASY-FIT Used to identify parameters in explicit model functions, dynamic systems of equations (steadystate), Laplace transforms, ordinary differential equations, differential algebraic equations and one-dimensional partial differential equations. Proceeding from given experimental data. For example, observation times and measurements, the minimum least squares distances of measured data from a fitting criterion are computed, that may depend on the solution of the dynamic system. http://www.uni-bayreuth.de/departments/math/~kschittkowski/easy_fit.htm

EASY-FIT Version 3.37 (2004) Software for parameter estimation (data fitting, system identification, nonlinear regression) in ... explicit model functions Laplace transforms steady state systems ordinary differential equations (ODE) differential algebraic equations (DAE) one-dimensional, time-dependent partial differential equations (PDE) one-dimensional, partial differential algebraic equations (PDAE) Please see ... how to estimate parameters of a dynamic model in 4 steps some features numerical algorithms graphical user interface ... relevant publications How to get the software ... free demo version student version (reduced features) version for academic sites commercial version with additional support (presentation, extended support, installation, maintenance) For more details, evaluation version, temptative numerical tests, and model analysis contact the author Highlights since Version 3.0 ... coupled algebraic ordinary differential equations for PDAEs, e.g., to define implicit boundary conditions faster executables MODFIT.EXE and PDEFIT.EXE negative initial values for ODEs and PDEs, e.g., to handle models with unknown initial times

105. MathGrapher | The Mathematical Graphing Tool For Students, Scientists And Engine Mathematical graphing tool for 2D and 3D functions, data, nonlinear curve fitting and integration of coupled ordinary differential equations. http://www.mathgrapher.com/

A Windows based mathematical graphing tool for 2D and 3D Functions and Data, shaded surfaces, contour plots. Includes linear and nonlinear curve fitting. You may integrate and analyse systems of up to 20 coupled ordinary differential equations (ODE's). Analysis tools include power spectrum calculation and Poincare sections. You may use these tools to study chaos in dynamical systems. Introduction Mathematical graphing tool for 2D and 3D functions and data. Includes nonlinear curve fitting and integration of coupled ordinary differential equations (ODE's). Study chaos in dynamical systems. MathGrapher ranks between graphical calculators and full-fledged mathematical tools like Mathematica. It is powerfull, easy to use and will probably meet your demands for a price that consists of only 2 instead of 4 digits. A fully functional trial version of Mathgrapher has just been released. You are invited to download it. Install Mathgrapher, start the Demonstrations and see what Mathgrapher can do for you. Purchasing will be possible in a few weeks. Functions in 2D and 3D MathGrapher is a graphical calculator for functions of the form F(x) and F(x,y) containing up to 20 subfunctions and 150 numerical and 100 named constants. Cartesian as well as polar coordinates can be chosen and functions can be represented in patametrized form (2D). F(x,y) can be represented in 2D and 3D by Shaded surfaces, Contour plots and Cross-sections through Contourplots. In the 3D viewer you may rapidly vary the viewing angle, distance and shading of the 3D surface using your mouse.

106. Tom Kurtz Home Page University of Wisconsin Madison. Research interests include limit theorems for stochastic differential equations, particle representations of measure-valued processes, stochastic partial differential equations, filtering for Markov processes, large deviations and modeling of spatial point processes. http://www.math.wisc.edu/~kurtz/

Professor Thomas G. Kurtz Ph.D., 1967, Stanford University Professor of Mathematics and Statistics Office: FAX: kurtz@math.wisc.edu Mailing address: Department of Mathematics University of Wisconsin - Madison Lincoln Drive Madison WI Fall 2004 Courses Math 833 Topics in the Theory of Probability: Martingale Problems and Stochastic Equations for Markov Processes Stat 311 Introduction to Mathematical Statistics Opportunities for Probabilists Pre- and Postdoctoral Fellowships at Wisconsin Intern Program in Probability and Stochastic Processes June 23 - August 8, 2003 IMA Program on Probability and Statistics in Complex Systems September, 2003 – June, 2004 Seminars Probability Seminar Mathematics Colloquium Systems Seminar Statistics Seminar ... VIGRE Meetings LMS Durham Symposium: Markov Chains July 25 – August 4, 2003 University of Durham Workshop on Stochastic Partial Differential Equations , September 27 – October 2, 2003 , BIRS, Banff Midwest Probability Colloquium October , Northwestern University Conference on Stochastic Processes and Interacting Particle systems , December 12-14, ISI, Delhi Conference on Stochastic Networks July 19-24, 2004

107. Visual Differential Equation Solver Applet This java applet displays solutions to some common differential equations. Zip archive of this applet. Another differential equation applet. java@falstad.com. http://www.falstad.com/diffeq/

Sorry, you need a Java-enabled browser to see the simulation. This java applet displays solutions to some common differential equations. At the top of the applet you will see a graph showing a differential equation (the equation governing a harmonic oscillator) and its solution. Also you will see a red crosshair on the graph on the left side. This is the initial point; you set the location of this point by clicking the mouse. You can change the equation by selecting a different left hand side or right hand side using the popup menus. Underneath the popup menus are a variety of parameters which you can change by clicking on them and dragging to the left or right. Also you can click on the sign to flip it from plus to minus or minus to plus. Double-clicking on the sign will set the value to zero. Full Directions. The source. More applets. Zip archive of this applet. ... Another differential equation applet. java@ falstad.com

108. Центр Применений Maple Живые дифференциальные уравнения. differential equations in Maple. http://www.demapler.narod.ru

109. Interactive Differential Equations http://www.awlonline.com/ide/

110. Math Unit III: More On The Derivative And Differential Equations Exact definition of derivation and calculating the relationship of derivatives of related functions. http://dept.physics.upenn.edu/courses/gladney/mathphys/subsection3_1_1.html

Back to Contents! Next: Force Revisited Up: CONSERVING EQUATIONS Previous: CONSERVING EQUATIONS Math Unit III: More on the derivative and differential equations In the last unit, we discussed how mathematicians and scientists deal with quantities that change in ways other than linearly. The key idea turns out to be the rate of change of the quantity. The lowbrow way to measure the rate of change is to compute the average rate of change over a small interval. The high-class way to talk about change is to try to compute the derivative , or instantaneous rate of change In real-world situations, when one deals with measured data, it is often the case that the data has been measured only for certain specific values of the independent variable. Then, one can only compute average rates of change between the data points. But in mathematics, when one deals with abstractly-defined functions, it is possible to compute derivatives. Often, mathematical models are developed using derivatives, predictions are made based upon these mathematical models, and then experimental results are compared to the predictions to see how well the models reflect reality. 1. Review and extensions

111. Differential Equation - Wikipedia, The Free Encyclopedia Differential equation. An important special case is when the equations do not involve x. These differential equations may be represented as vector fields. http://en.wikipedia.org/wiki/Differential_equation

Differential equation From Wikipedia, the free encyclopedia. In mathematics , a differential equation is an equation that describes the relationship between an unknown function and its derivatives . The order of a differential equation describes the most times any function in it has been differentiated. (See differential calculus and integral calculus Table of contents 1 Definition 2 General application 3 History 3.1 Linear ODEs with constant coefficients ... edit Definition Given that y is a function of x and that denote the derivatives an ordinary differential equation (ODE) is an equation involving The order of a differential equation is the order n of the highest derivative that appears. When a differential equation of order n has the form it is called an implicit differential equation whereas the form is called an explicit differential equation. A differential equation not depending on x is called autonomous edit General application An important special case is when the equations do not involve x . These differential equations may be represented as vector fields . This type of differential equations has the property that space can be divided into equivalence classes based on whether two points lie on the same solution curve . Since the laws of physics are believed not to change with time, the physical world is governed by such differential equations. (See also

112. Arieh Iserles University of Cambridge. Research interests in numerical ordinary differential equations; also functional equations, approximation theory, special functions, numerical partial differential equations, nonlinear algebraic equations and nonlinear dynamical systems. http://www.damtp.cam.ac.uk/user/na/people/Arieh/

113. Differential Equation - Wikipedia, The Free Encyclopedia (Redirected from differential equations). Therefore, the study of differential equations is a wide field in both pure and applied mathematics. http://en.wikipedia.org/wiki/Differential_equations

Differential equation From Wikipedia, the free encyclopedia. (Redirected from Differential equations In mathematics , a differential equation is an equation that describes the relationship between an unknown function and its derivatives . The order of a differential equation describes the most times any function in it has been differentiated. (See differential calculus and integral calculus Table of contents 1 Definition 2 General application 3 History 3.1 Linear ODEs with constant coefficients ... edit Definition Given that y is a function of x and that denote the derivatives an ordinary differential equation (ODE) is an equation involving The order of a differential equation is the order n of the highest derivative that appears. When a differential equation of order n has the form it is called an implicit differential equation whereas the form is called an explicit differential equation. A differential equation not depending on x is called autonomous edit General application An important special case is when the equations do not involve x . These differential equations may be represented as vector fields . This type of differential equations has the property that space can be divided into equivalence classes based on whether two points lie on the same solution curve . Since the laws of physics are believed not to change with time, the physical world is governed by such differential equations. (See also

114. DDE-BIFTOOL A MATLAB package for bifurcation analysis of delay differential equations. http://www.cs.kuleuven.ac.be/~koen/delay/ddebiftool.shtml

DDE-BIFTOOL: a Matlab package for bifurcation analysis of delay differential equations Koen Engelborghs Tatyana Luzyanina, Giovanni Samaey K.U.Leuven, Department of Computer Science Celestijnenlaan 200A B-3001 Leuven Belgium Functionality: DDE-BIFTOOL is a Matlab package for numerical bifurcation analysis of delay differential equations with several fixed discrete and/or state-dependent delays. It allows the computation, continuation and stability analysis of steady state solutions, their Hopf and fold bifurcations, periodic solutions and connecting orbits (but the latter only for the constant delay case). Stability analysis of steady state solutions is achieved through computing approximations and corrections to the rightmost characteristic roots. Periodic solutions, their Floquet multipliers and connecting orbits are computed using piecewise polynomial collocation on adapted meshes. Text material: DDE-BIFTOOL was started as a part of the PhD of its first author under supervision of Prof. Dirk Roose. The package and it's use are described in the manual . A preprint [2] includes additional examples and comments. A brief description of the numerical methods used and additional references are included in [ Current version: DDE-BIFTOOL v. 2.02 is now available!! Find

115. Partial Differential Equation Toolbox 1.0.4 resulting system of equations using MATLAB s proven sparse matrix solver (\) and a stateof-the-art stiff solver from the Ordinary differential equations Suite http://www.comsol.se/products/pde/

Hem Produkter MATLAB Priser Kurser Seminarier Tekniskt kundstöd Konsultation Erbjudanden The Partial Differential Equation (PDE) Toolbox extends the MATLAB technical computing environment with powerful and flexible tools for the study and solution of PDEs in two-space dimensions (2-D) and time. The PDE Toolbox provides a set of command line functions and a graphical user interface for preprocessing, solving, and postprocessing generic 2-D PDEs using the Finite Element Method (FEM). Visualization of temperature and heat flux using the PDE Toolbox. This fundamental approach facilitates the use of nonconstant coefficients, specific nonlinearities, the use of subdomains, and n-dimensional systems (dependent variables) - all specified using the familiar MATLAB command line syntax. PDEs are used as mathematical models for phenomena in all branches of engineering and science. For example, the elliptic and parabolic equations can be used for steady and unsteady heat transfer in solids, for flow in porous media and diffusion problems, for steady electrostatics of dielectric and conductive media, and for potential flow. The hyperbolic PDE is used for transient and harmonic wave propagations in acoustics and electromagnetics, and for transverse motions of membranes. The elliptic system of PDEs can be used to solve plane stress and plane strain problems in structural mechanics. Complete GUI for pre- and post-processing 2-D PDEs Automatic and adaptive meshing Geometry creation using constructive solid geometry (CSG) paradigm

116. Volterra A short biography on Volterra and his work in differential equations and mathematical physics. http://www-groups.dcs.st-and.ac.uk/~history/Mathematicians/Volterra.html

Vito Volterra Born: 3 May 1860 in Ancona, Papal States (now Italy) Died: 11 Oct 1940 in Rome, Italy Click the picture above to see six larger pictures Show birthplace location Previous (Chronologically) Next Biographies Index Previous (Alphabetically) Next Main index Vito Volterra 's interest in mathematics started at the age of 11 when he began to study Legendre 's Geometry. At the age of 13 he began to study the Three Body Problem and made some progress by partitioning the time into small intervals over which he could consider the force constant. His family were extremely poor (his father had died when Vito was two years old) but after attending lectures at Florence he was able to proceed to Pisa in 1878. At Pisa he studied under Betti , graduating Doctor of Physics in 1882. His thesis on hydrodynamics included some results of Stokes , discovered later but independently by Volterra. He became Professor of Mechanics at Pisa in 1883 and, after Betti 's death, he occupied the Chair of Mathematical Physics. After being appointed to the Chair of Mechanics at Turin he was appointed to the Chair of Mathematical Physics at Rome in 1900. Volterra conceived the idea of a theory of functions which depend on a continuous set of values of another function in 1883.

117. The 2002 UAB International Conference On Differential Equations And Mathematical The 2002 UAB International Conference on differential equations and Mathematical Physics Birmingham, Alabama March 2630, 2002. Talks http://www.math.uab.edu/uab02/

The 2002 UAB International Conference on Differential Equations and Mathematical Physics Birmingham, Alabama March 26-30, 2002 Talks of 25 minutes in length in all areas of differential equations and mathematical physics are invited. An online registration form is available here (the deadline is March 1, 2002). Please visit this site for updates, or send us an email if you have any questions. Click here to put yourself on the mailing list (registering automatically puts you on the mailing list). Program Plenary Speakers M. Aizenman, Princeton University J. Glimm, SUNY at Stony Brook S. Jitomirskaya, UC Irvine A. Laptev, KTH, Stockholm J. Lebowitz, Rutgers University E. Lieb, Princeton University T.-P. Liu, Stanford University and Academia Sinica (Taiwan) C.-A. Pillet, Univ. de Toulon, CPT-CNRS/FRUMAM R. Weder, UNAM, Mexico City General Sessions General sessions will be open for registered participants. Click here to access our online registration form (the deadline is March 1, 2002). Focus Sessions Talks in the Focus Sessions are by invitation of the organizers (listed in parentheses). Conservation Laws (G.-Q. Chen, Northwestern University)

118. Horwitz, Alan Professor of mathematics at the Delaware County Campus of Penn State University in Media, PA. His research interests polynomial interpolation, numerical integration, algebraic differential equations, means, and ratios of polynomials with real zeros. http://www.math.psu.edu/horwitz/

119. Calculus@Internet Web Page Links 1 through 25. Modeling Population Growth - differential equations allow us to mathematically model quantities that change continuously in time. http://www.calculus.net/ci2/search/?request=category&code=18&off=0&tag=920043892

120. Linear Methods Textbook suitable for a first course on partial differential equations, Fourier series and special functions, and integral equations by Evans M. Harrell II and James V. Herod. HTML, RTF and PDF with Maple and Mathematica worksheets. http://www.mathphysics.com/pde/

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