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Summary

WebCab Functions (J2SE Edition) by WebCab

URLs: webcab-functions-j2se, webcab functions j2se, webcabfunctionsj2se, webcab

Java API Components offering refined numerical procedures to either construct a function of one or two variables from a set of points (i.e. interpolate), or solve an equation of one variable. WebCab Functions (J2SE Edition) includes interpolation procedures such as Newton polynomials, Lagrange's formula, Burlisch-Stoer algorithm, Cubic splines (natural and free), Bicubic interpolation and procedures for find the interpolation functions coefficients.

This suite includes the following features:

Interpolation Module

Polynomial Interpolation and extrapolation

Lagrange's formula - for interpolating a function known at N points with a polynomial of degree N-1

Burlisch-Stoer algorithm - interpolates functions using rational functions, this method gives error estimates

Cubic Splines - we give algorithms for natural and clamped cubic splines

Sorting - efficient techniques are used for finding tabulated values

Coefficients of an Interpolating Polynomial

Matrix method - this method relies upon diagonalizing a matrix (or solving a system of equations), and is of the order N squared

Zero method - by evaluating the interpolating polynomial at particular values we deduce the coefficients, this method is of the order N cubed

Interpolation and extrapolation in two or more dimensions

Grid - functions can be interpolated on an n-dimensional grid

Bilinear interpolation - we consider a multidimensional interpolation by breaking the problem into successive one dimensional interpolations

Accuracy - the use of higher order polynomials to obtain increased accuracy

Smoothness - the use of higher order polynomials to enforce smoothness on some of the derivatives

Bicubic interpolation - finds an interpolating function with a specified derivatives and cross derivatives which vary smoothly at the grid points

Bicubic spline - a special case of Bicubic interpolation involving the use of successive one-dimensional splines

Equation Solver Module

Interval Bisection Method - A robust method that always finds a solution or a singularity inside a bracketed interval.

Secant Method - Generally this procedure converges and is much faster than the interval bisection method.

Brent's Algorithm - The method of choice to find a bracketed root of a one dimensional equation when you cannot easily compute the function's derivative.

Ridders' Method - Concise and almost as reliable as Brent's Algorithm for finding a bracketed root of an equation.

Method of Regula Falsi - This procedure uses a slight alteration on the secant method to ensure convergence. The procedure is generally faster than the interval bisection method and slightly slower than the secant method.

Newton-Raphson Method - Given a first approximation to a root and the differential of the function this procedure will always produce a solution. We implement this procedure for polynomial functions of one variable.

Fail-Safe Newton-Raphson Method - This method combines the Newton-Raphson method and the Interval Bisection Method in order to produce very stable and fast convergence. Given a first approximation to a root and the differential of the function this procedure will always produce a solution.

This product also contains the following features:

GUI Bundle - we bundle a suite of graphical user interface JavaBean components allowing the developer to plug-in a wide range of GUI functionality (including charts/graphs) into their client applications.

JDBC Mediator - A J2SE Component which mediates between a J2SE component, its J2SE Clients and the Database server. The JDBC Mediator J2SE classes are a convenient way of enhancing all financial and mathematical specific methods with JDBC-based functionality. Check the jdbc subpackage of every J2SE class for JavaDocs documentation.

Web Application Example - A Java WAR file which contains a JSP example that makes use of the functionality provided by our J2SE Component.

Synthetic JDBC - The JDBC functionality provided by the Web Application example included within this package. This Web Application is an example of how to make a JSP client using our J2SE Component while manually implementing the JDBC code. The JSP Application applies J2SE methods to certain rows from the database and lists the output in HTML format.

Java API Components offering refined numerical procedures to either construct a function of one or two variables from a set of points (i.e.

Pricing: WebCab Functions (J2SE Edition) V2.0 1 Developer License, WebCab Functions (J2SE Edition) V2.0 4 Developer Team License, WebCab Functions (J2SE Edition) V2.0 1 Site Wide License (Allows Unlimited Developers at a Single Physical Address)

Evals & Downloads: Read the WebCab Functions documentation - Requires Acrobat Reader, Download the WebCab Functions (J2SE Edition) evaluation on to your computer - Expires after 100 uses

Operating System for Deployment: Windows XP, Windows Server 2003, Windows 2000, Windows 98, Sun Solaris 9, Linux Kernel V2.4.x, RedHat Linux 7.x

Architecture of Product: 32Bit

Product Type: Component

Component Type: JavaBean, Java Class

Compatible Containers: JBuilder X, JBuilder 9, JBuilder 7, JBuilder 6, Oracle 9i JDeveloper, NetBeans IDE 3.x, Sun ONE Studio 5 (Formerly FORTE Compiler Collection), WebLogic Workshop

Product Class: Business Components

Keywords: interpolation cubic spline equation solver

Math Stats Mathematics Mathematical Statistic Statistical

Part numbers: PC-515471-51267 515471-51267 PC-515471-51268 515471-51268 PC-515471-51269 515471-51269