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C. Drake P. | Drake's Research Blag

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C. Drake P. | Drake's Research Blag | cdrakep.wordpress.com Reviews

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Weekly Update 09/20 | C. Drake P.

https://cdrakep.wordpress.com/2009/09/21/weekly-update

Drake's Research Blag. Leave a comment ». I started out the week playing with the predator prey function. I explored how to translate my existing programs into ‘auto-test’ programs. I finished the week training neural networks. Read more about it in the write up, if the link works. It doesn’t seem to for me. Weekly Write Up 9/20. When I go to media, and insert the PDF it comes out like this :. Weekly Write Up 9/20. September 21, 2009 at 4:10 am. Posted in CSUMS Weekly Updates. Leave a Reply Cancel reply.

2

December | 2009 | C. Drake P.

https://cdrakep.wordpress.com/2009/12

Drake's Research Blag. Archive for December 2009. Leave a comment ». Tomorrow is poster day for CSUMS. Here is the PDF for my and Chris’s poster. Poster for Numerical Characterization of Entropy Data. The main focus of our project was verifying that the Entropy Key. So basically our conclusion, in statistical terms, yes the Entropy Key is random. It has not failed the null hypothesis test. That is about all that can be said given the nature of randomness. December 13, 2009 at 9:50 pm.

3

November | 2009 | C. Drake P.

https://cdrakep.wordpress.com/2009/11

Drake's Research Blag. Archive for November 2009. Leave a comment ». November 18, 2009 at 9:08 pm. Blog at WordPress.com. Create a free website or blog at WordPress.com.

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Poster Report. | C. Drake P.

https://cdrakep.wordpress.com/2009/12/13/poster-report

Drake's Research Blag. Leave a comment ». Tomorrow is poster day for CSUMS. Here is the PDF for my and Chris’s poster. Poster for Numerical Characterization of Entropy Data. The main focus of our project was verifying that the Entropy Key. So basically our conclusion, in statistical terms, yes the Entropy Key is random. It has not failed the null hypothesis test. That is about all that can be said given the nature of randomness. December 13, 2009 at 9:50 pm. Laquo; i win. Leave a Reply Cancel reply.

5

October | 2009 | C. Drake P.

https://cdrakep.wordpress.com/2009/10

Drake's Research Blag. Archive for October 2009. Weekly writeup for 10/27. Leave a comment ». Well, waited on some results from all my terminal monkeying. Wrote a bunch of programs and scripts to manipulate data. Made a lot of graphs. A big thanks to the 20 cores over 5 computers that resulted in roughly 3 months of computation over the last two or three weeks. Most of the work over the last couple weeks relied heavily on Chris’s OpenMP Auto-Correlation code. For Your Consideration, Write Up the Third.

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About | Math Stuff

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Skip to search - Accesskey = s. This is a blog. I will use it for classes at the University of Massachusetts Dartmouth. Leave a Reply Cancel reply. Enter your comment here. Fill in your details below or click an icon to log in:. Address never made public). You are commenting using your WordPress.com account. ( Log Out. You are commenting using your Twitter account. ( Log Out. You are commenting using your Facebook account. ( Log Out. You are commenting using your Google account. ( Log Out.

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Fixed Point Iteration | Math Stuff

https://ceedeepee.wordpress.com/2009/12/06/fixed-point-iteration

Skip to search - Accesskey = s. Posted in MTH 361 - Numerical Analysis. By cdrakep on December 6, 2009. Fixed Point Iteration is a method of finding fixed points of iterated functions. A fixed point is defined as. Or, the value given is also that which is returned by the function. Graphically fixed point iteration looks something like this. Fixed Point Iteration on Cos(x .5). There is nothing that says all functions must have a fixed point. All functions. Is a constant and. When working on the. Be a sequ...

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Polynomial Interpolation | Math Stuff

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Skip to search - Accesskey = s. The functions we’re going to be interpolating are those which have a domain and range both in. And the graph must lie in. We’re going to be interpolating functions given several points, which will serve as an estimate for a function, say. A Lagrange interpolating polynomial of degree. Or less given at least. Decreasing on the domain,. Should be under the capital pi, wordpress latex. Is true. It’s easy to check this polynomial, no other. Alternativel use x=linspace(0,2*pi,N).

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Quadrature | Math Stuff

https://ceedeepee.wordpress.com/2009/12/09/quadrature

Skip to search - Accesskey = s. Posted in MTH 361 - Numerical Analysis. By cdrakep on December 9, 2009. Quadrature as used in numerical analysis, is the method by which we integrate our interpolated functions thereby finding a numerical approximation to the integral through a polynomial instead of the potentially hard to find integral of the original or unknown function,. Basic quadrature is estimating the value of the integral based on a formula that looks like :. While these functions are easy, they&#8...

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Root Finding | Math Stuff

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Skip to search - Accesskey = s. Root finding is a numerical method of finding the zeros of a function,. The Actual Method of N-Sectioning. Running the original bisection code on. I know that to. Significant digits I need. Sectioning the same domain to. The code finds that there is no zero on. One calculation) and then proceeds to find the zero on. Further sectioning, we have the sub-domains. Code runs, nothing on. One calculation), nothing on. Two calculations), hit on. Finding the zero in. It seems like...

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Larange Interpolation with/out Vandermonde Matrices | Math Stuff

https://ceedeepee.wordpress.com/2009/12/08/larange-interpolation-with-vandermonde-matrices

Skip to search - Accesskey = s. Larange Interpolation with/out Vandermonde Matrices. Posted in MTH 361 - Numerical Analysis. By cdrakep on December 8, 2009. The functions we’re going to be interpolating are those which have a domain and range both in. And the graph must lie in. We’re going to be interpolating functions given several points, which will serve as an estimate for a function, say. A Lagrange interpolating polynomial of degree. Or less given at least. Decreasing on the domain,. Cos(x) with Int...

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Newton’s Polynomial… Divided Difference Interpolation | Math Stuff

https://ceedeepee.wordpress.com/2009/12/08/newtons-polynomial-divided-difference-interpolation

Skip to search - Accesskey = s. Newton’s Polynomial… Divided Difference Interpolation. Posted in MTH 361 - Numerical Analysis. By cdrakep on December 8, 2009. Since I’m a sucker for punishment I decided to ignore all the fabulous code available on the internet, and the code provided in class, and attempt to write my own program for interpolating using Newton’s Divided Difference. Now with the red line being the actual function values, and the green boxes my interpolated polynomial’s values, for. A(k,j 1)...

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Quadrature | Math Stuff

https://ceedeepee.wordpress.com/quadrature

Skip to search - Accesskey = s. Quadrature as used in numerical analysis, is the method by which we integrate our interpolated functions thereby finding a numerical approximation to the integral through a polynomial instead of the potentially hard to find integral of the original or unknown function,. Basic quadrature is estimating the value of the integral based on a formula that looks like :. A more accurate numerical approximation to the integral is Simpson’s Rule. While these functions are easy, they...

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Newton’s Method | Math Stuff

https://ceedeepee.wordpress.com/2009/12/07/newtons-method

Skip to search - Accesskey = s. Posted in MTH 361 - Numerical Analysis. By cdrakep on December 7, 2009. Newton’s method is probably the best known method for finding approximations to the roots of a function. Newton’s method can converge quickly, and will usually converge no matter what the initial guess is, but if the initial guess is close it will converge in fewer iterations. Say you have a real valued function. Is a root of the equation. Using the following algorithm. Start with a point. This method ...

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C. Drake P. | Drake's Research Blag

Drake's Research Blag. Leave a comment ». Tomorrow is poster day for CSUMS. Here is the PDF for my and Chris’s poster. Poster for Numerical Characterization of Entropy Data. The main focus of our project was verifying that the Entropy Key. So basically our conclusion, in statistical terms, yes the Entropy Key is random. It has not failed the null hypothesis test. That is about all that can be said given the nature of randomness. December 13, 2009 at 9:50 pm. Leave a comment ». November 18, 2009 at 9:08 pm.

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Chris (cd) is a firm believer in education and helping others. He co-founded a successful computer mentorship program, which he is currently working on developing into an on-line curriculum. For the greater part of two decades he has been working as a Linux professional. He currently holds advanced certifications from Red Hat. In his (remaining) spare time, he writes media criticism, technical manuals, and illustrated stories. She has made many websites including the one you are currently looking at (hey!

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