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 Visit neurosolutions.com | Download Evaluation |
Volume 8, No.5 |
| This is a Neurosolutions Newsletter, which you are receiving because you requested to stay informed about new developments at NeuroDimension. You can also access current and past issues of Neurosolutions Newsletters online. |
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| Holiday Sale - Save 15% on NeuroSolutions Products!
NeuroDimension is excited to offer the Happy Holidays Sale! From now through December 31st, all NeuroDimension software can be purchased at 15% off the regular list prices.
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This is an excellent time to purchase NeuroSolutions, TradingSolutions, a NeuroSolutions or TradingSolutions add-on, or one of our genetic products!
But don't wait too long - this offer ends December 31, 2008. Use offer code ##### when placing your order. You can place your order now using our online order entry system at http://www.neurosolutions.com/order/
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| Spring '09 Neural Network Course Announced!
The next neural network course has been scheduled for June 15 - June 19, 2009 at the Embassy Suites in Orlando, Florida. This course always fills up fast, so be sure to sign up today!
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Our course format allows both novice and advanced users to find a suitable course.
Offered courses include: "Introduction to NeuroSolutions", "Fundamentals of Neural Networks and NeuroSolutions", and "Advanced NeuroSolutions". The courses include a copy of our interactive book, "Neural and Adaptive Systems: Fundamentals Through Simulations". For more information, click the "More Info" button below.
You can watch this video on the website by clicking the "More Info" button.
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 NS Tip Box: Levenberg-Marquardt
This NeuroSolutions Tip Box video demonstrates one of the most significant enhancements made in NeuroSolutions 5.0, the addition of the Levenberg-Marquardt learning algorithm. Levenberg-Marquardt (LM) is one of the most efficient higher-order adaptive algorithms known for minimizing the MSE of a neural network.
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What is Levenberg-Marquardt?
It is a member of a class of learning algorithms called "pseudo second order methods". Standard gradient descent algorithms use only the local approximation of the slope of the performance surface (error versus weights) to determine the best direction to move the weights in order to lower the error. Second order methods use the Hessian or the matrix of second derivatives (the curvature instead of just the slope) of the performance surface to determine the weight update, while pseudo-second order methods approximate the Hessian in order to reduce the processing time required.
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You can watch this video on the website by clicking the "More Info" button.
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| Customer Interview: Snow Fall Prediction for National Weather Service
Mr. Paul Roebber has been using NeuroSolutions along with the Custom Solution Wizard and Source Code Library for the past 8 years. Using NeuroSolutions, Mr. Roebber developed a snow density system that is currently employed by the National Weather Service to assist in the prediction of snow fall depths.
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Mr. Roebber’s approach correctly diagnoses 60.4% of the snow event cases examined, which is a substantial improvement over the 41.7% correct using the sample climatology, 45% correct using the 10-to-1 ratio, and 51.7% correct using the National Weather Service "new snowfall to estimated meltwater conversion" table. The Heidke skill score measures the fraction of correct forecasts after eliminating those forecasts which would be correct due purely to random chance. Mr. Roebber’s approach attains Heidke skill scores of 0.34 - 0.42, which is an increase of 75% - 183% over the next most skillful approach!
To read the complete interview, please click the "More Info" button below
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| New Web Content Overview
New content is always being added to our websites. Here is some of the latest content of interest to our users:
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