Wolfram Research Mathematica 8.0.4.0 With Add-ons

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Wolfram Research Mathematica 8.0.4.0 With Add-ons | MacOSX | 1.1 GB 200 MB
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Almost any workflow involves computing results, and that's what Mathematica doesfrom building a hedge fund trading website or publishing interactive engineering textbooks to developing embedded image recognition algorithms or teaching calculus.
And Extend Mathematica's functionality through Mathematica Applications, which are available for many specific functions.
Mathematica is renowned as the world's ultimate application for computations. But it's much moreit's the only development platform fully integrating computation into complete workflows, moving you seamlessly from initial ideas all the way to deployed individual or enterprise solutions.

With more than 20 years of experience and millions of users from Fortune 500 companies to government departments to thousands of universities worldwide, Mathematica technology lies behind many of the world's most impressive projects, processes, and organizationsand your future innovation?

In Wolfram Mathematica Add-ons included:

- Neural Networks 1.0
Artificial neural networks have revolutionized the way researchers solve many complex and real-world problems in engineering, science, economics, and finance. Neural Networks capitalizes on the computational power and flexibility of Mathematica to help you utilize this cutting-edge technology.
Neural Networks gives professionals and students the tools to train, visualize, and validate neural network models. It supports a comprehensive set of neural network structures?including radial basis function, feedforward, dynamic, Hopfield, perceptron, vector quantization, unsupervised, and Kohonen networks. It implements state-of-the-art training algorithms like Levenberg-Marquardt, Gauss-Newton, and steepest descent. Neural Networks also includes special functions to address typical problems in data analysis, such as function approximation, classification and detection, clustering, nonlinear time series, and nonlinear system identification problems.

- Time Series 1.4
Time Series performs univariate and multivariate analysis and enables you to explore both stationary and nonstationary models. You can select a model to fit your data and obtain estimates of the model's parameters. Choose from standard methods such as Yule-Walker, Levinson-Durbin, long autoregression, Hannan-Rissanen, and others.
After reading in and plotting your data, use the built-in Time Series transforms for linear filtering, simple exponential smoothing, differencing, moving averages, and more to transform your raw data into a form suitable for modeling. Calculating and plotting the correlation and partial correlation functions will help you spot patterns. Once you select a model to fit your data, Time Series makes it easy to estimate the model parameters and check its validity using residuals and tests such as the portmanteau, turning points, difference-sign, and others.

- Link for Excel 3.1
With Mathematica Link for Excel, you can have it all: All of the power and sophistication of Mathematica. All of the familiarity and convenience of Excel. Mathematica Link for Excel eliminates the complexities of bridging the two programs, giving you the best of both worlds.
Mathematica Link for Excel adds over a thousand functions and options to Excel and lets you interactively explore them using the Mathematica function wizard. Excel formulas can suddenly perform symbolic computations, find complex roots, plot equations, and much more. Displaying Mathematica graphics and typesetting equations in Excel is as easy as entering a formula. Data and equations can be visualized in new and insightful ways that are not possible in Excel alone.

- Finance Essentials 1.2
Software Wolfram Mathematica Finance Essentials is specially designed for stockbrokers, financial analysts, brokers and other financial sector professionals, involved in data analysis and modeling strategies. This package can be used to quickly create a custom application, test and evaluate strategies for hedging and trading value assets using the capital asset pricing model(CAPM).
Finance Essentials works with major financial entities (such as cash flows, option, bond, interest rate) and functions (such as the conversion rate of interest assessment option, a measure of sensitivity) and offers an effective way to use them.

Examples help you easily calculate Markowitz efficient portfolio and the moving average.

- Wavelet Explorer 1.2.2
Software Wolfram Mathematica Wavelet Explorer greatly extends the capabilities of Mathematica with a convenient and functional tools for wavelet-analysis used in the study and research different spheres of knowledge - from signal and image processing to analyze statistical data. Wavelet Explorer offers many tools wavelet - analysis. Ready-to-use functions and utility applications Wavelet Explorer allow you to apply a lot of wavelet - transformation to different projects, to generate commonly used filters such as Daubechies' extremal phase, Least asymmetric, Coiflets, Spline and a number of drugih.Krome impressive set of powerful tools for analysis and visualization, Wavelet Explorer is an excellent interactive tutorial on wavelet-analysis for beginners. Examples of previous theoretical calculations and methods for studying the properties of wavelet-and then shows how you can apply methods of wavelet-analysis in various fields of knowledge.

- Parallel Computer Toolkit 2.1.0
Parallel Computing Toolkit software is designed to meet the challenges of using parallel computing, and application design. Parallel Computing Toolkit contains many standard primitives of concurrent programming and includes high-level commands for parallel execution of operations. Package allows you to write platform-independent application that can run on any computer where the program is installed Mathematica.
Parallel Computing Toolkit is designed for engineers, scientists and analysts, who have used it for solving complex problems. Teachers educational institutions use this program to demonstrate various aspects of parallel computing in the classroom.


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