Match n Freq 6.10

Pulse shaping filter program that finds the pole-zero locations of a transfer function, H(s), for a matched filter. H(s) equals a -desired- signal (Yout) divided by a given input signal (Yin). Both Yout and Yin are functions of frequency. Group delay may also be calculated to compliment a given data set, thus, providing a flat group delay. Another improved productivity example do to using Calculus (level) programming.

Match n Freq 6.10

Pulse shaping filter program that finds the pole-zero locations of a transfer function, H(s), for a matched filter. H(s) equals a -desired- signal (Yout) divided by a given input signal (Yin). Both Yout and Yin are functions of frequency. Group delay may also be calculated to compliment a given data set, thus, providing a flat group delay. Another improved productivity example do to using Calculus (level) programming.

Match n Freq 6.10

Pulse shaping filter program that finds the pole-zero locations of a transfer function, H(s), for a matched filter. H(s) equals a -desired- signal (Yout) divided by a given input signal (Yin). Both Yout and Yin are functions of frequency. Group delay may also be calculated to compliment a given data set, thus, providing a flat group delay. Another improved productivity example do to using Calculus (level) programming.

Match n Freq 6.10

Pulse shaping filter program that finds the pole-zero locations of a transfer function, H(s), for a matched filter. H(s) equals a -desired- signal (Yout) divided by a given input signal (Yin). Both Yout and Yin are functions of frequency. Group delay may also be calculated to compliment a given data set, thus, providing a flat group delay. Another improved productivity example do to using Calculus (level) programming.

Match n Freq 6.10

Pulse shaping filter program that finds the pole-zero locations of a transfer function, H(s), for a matched filter. H(s) equals a -desired- signal (Yout) divided by a given input signal (Yin). Both Yout and Yin are functions of frequency. Group delay may also be calculated to compliment a given data set, thus, providing a flat group delay. Another improved productivity example do to using Calculus (level) programming.

ChemMaths 15.5

ChemMaths is a engineering,mathematical and chemistry program. Software suitable for Engineering,Chemistry/Science Professionals and educational use. Contains information on 3000+ chemical compounds,allows predition of chemical compound properties,critical constants, thermodynamic properties etc,periodic table, solves 400+ chemical/electrical/mechcanical engineering, phyics, and mathematical equations. Contains 200+ unit conversions & more.

SpectrumSolvers 6.10

Find best Spectral Estimation Method for a Power Spectral Density plot. A menu of 10+ spectral estimators from Steve Kay's textbook 'Modern Spectral Estimation' 1988 is available to choose from. The results differ dramatically from one estimator to another. Plus, varying input parameters and/or number of points may provide discrepancies. Observe how zero padding effects your results. See 50+ dB weak signal detection.

MEPX 2015.05.22

MEPX - a complex data analysis software running on Windows, Mac OSX and Linux Ubuntu. It is used for solving regression and classification problems. MEPX is based on Multi Expression Programming which is actually an evolutionary algorithm capable of generating computer programs in an automatic way. Models for regression and binary classification problems can be easily obtained.

SRS1 Cubic Spline for Excel 2.51

This is free software that adds several spline and linear interpolation functions to Microsoft Excel. It is simple to use because the new functions work just like all other existing Excel functions. The new functions can be used for data analysis, forecasting, and many other applications. See http://www.SRS1Software.com for demos and more information.

Regression Analysis and Forecasting 3.0

The Multiple Regression Analysis and Forecasting model provides confidence in identifying value drivers and forecasting business plan and scientific data. While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies.

Regression Analysis and Forecasting 3.0

The Multiple Regression Analysis and Forecasting model provides confidence in identifying value drivers and forecasting business plan and scientific data. While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies.

Regression Analysis and Forecasting 3.0

The Multiple Regression Analysis and Forecasting model provides confidence in identifying value drivers and forecasting business plan and scientific data. While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies.

Regression Analysis and Forecasting 3.0

The Multiple Regression Analysis and Forecasting model provides confidence in identifying value drivers and forecasting business plan and scientific data. While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies.

Regression Analysis and Forecasting 3.0

The Multiple Regression Analysis and Forecasting model provides confidence in identifying value drivers and forecasting business plan and scientific data. While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies.

Regression Analysis and Forecasting 3.0

The Multiple Regression Analysis and Forecasting model provides confidence in identifying value drivers and forecasting business plan and scientific data. While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies.

Regression Analysis and Forecasting 3.0

The Multiple Regression Analysis and Forecasting model provides confidence in identifying value drivers and forecasting business plan and scientific data. While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies.

Regression Analysis and Forecasting 3.0

The Multiple Regression Analysis and Forecasting model provides confidence in identifying value drivers and forecasting business plan and scientific data. While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies.

Regression Analysis and Forecasting 3.0

The Multiple Regression Analysis and Forecasting model provides confidence in identifying value drivers and forecasting business plan and scientific data. While it utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies.

FasteR 0.4.1

FasteR Desktop is a combination of GUI and IDE for R statistical language. FasteR Desktop is stand-alone independent application for R. This application allows you to use mutliple tools and features for produsing R code.

AcaStat Mac 8.3.10

AcaStat statistical software is an inexpensive and easy-to-use data analysis tool. Create and analyze crosstabulations, descriptive statistics, basic significance tests, and summary reports. Ideal for those who need a low-cost alternative for producing basic summary statistics at school or work. Create data files or import from spreadsheets or statistical software. Practice data files. Integrated update module. Available in Mac and Windows.

MITCalc - Torsion Springs 1.20

The calculation is intended for the purposes of geometric and strength designs of spiral cylindrical torsion springs made of wires and rods in circular sections, loaded with a static or cyclic loading. Application is developed in MS Excel, is multi-language and supports Imperial and Metric units. Is based on ANSI, ISO and DIN standards and support many 2D and 3D CAD systems.

MITCalc - Technical Formulas 1.19

Solutions to dozens of basic formulas from physics, technology and mechanical engineering. Help, pictures as well as many selection tables with values of various coefficients and material properties are available for the formulas. This module also includes a workbook with conversion of units and many technical tables. Application is developed in MS Excel, is multi-language and supports Imperial and Metric units.

NeuroXL Package 4.0.5

NeuroXL Package is a neural network toolkit for Microsoft Excel. It consists of NeuroXL Predictor and NeuroXL Clusterizer. NeuroXL Predictor is designed for forecasting and estimating numeric amounts such as sales, prices, etc. Its ability to discover non-linear relationships in input data makes it ideally suited for forecasting dynamic systems like the stock market. NeuroXL Clusterizer is designed for data cluster analysis in Microsoft Excel.

NeuroXL Predictor 4.0.5

NeuroXL Predictor is a neural network forecasting tool that quickly and accurately solves forecasting, classification and estimation problems in Microsoft Excel. It is designed from the ground-up to aid experts in solving real-world forecasting problems. NeuroXL Predictor interface is easy-to-use and intuitive, does not require any prior knowledge of neural networks, and is integrated seamlessly with Microsoft Excel.

NeuroXL Clusterizer 4.0.5

NeuroXL Clusterizer is a neural network data cluster analysis add-in for Microsoft Excel. NeuroXL Clusterizer is designed for clustering data in Microsoft Excel. Its ability to handle numerous, often-interrelated variables makes it an excellent "data mining" tool. NeuroXL Clusterizer can be applied to solve problems in numerous industries and disciplines, including finance, business, medicine, and research science.

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