Search Results for "progressive"
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Showing 4 open source projects for "progressive"
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Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Function Point Analysis
Progressive Function Point Analysis Workbook in Excel
Progressive Function Point Analysis Book Released: Print Copy: http://www.amazon.com/Progressive-Function-Point-Analysis-Estimation/dp/1502354160 EBook: http://www.amazon.com/dp/B00NH0MMAG Please support this project and its future releases ! Managers provide the architect/teams with project requirements. The architect/team returns detailed task list with estimated man hours per task making life easier for Project Managers with less guesstimates and proper business/technical process flows to justify estimates. ... -
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n-chinese-remainders
chinese remainder theorem - progressive solving, n-soln, extras
"chinese remainder" solves a system of equations over modulus quickly. crtwo is an improvement to Mathematica's release. crtwo: solves Chinese Remainder a pair at a time, (uses gcd), yet is still fast. Which means crtwo, unlike text book soln, uses an algorithm to solve or fail one mod equation at a time. showing win or fail of each eqn and solving other sawtooth intersections is possible, due to that. crAll2@crtwo provides n soln near x for CR using width of soln crchart3... -
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eANN
eANN is an implementation of several kind of neural networks.
eANN is an implementation of several kind of neural networks written with the intention of providing a (hopefully) easy to use, and easy to modify, OOP source code. It is possible to have several different sized networks running simultaneously, each functioning independently of the others or acting as inputs between them. It also easy to modify the structure so that neurons (or even whole layers) can be created/pruned during simulation allowing dynamic expansion/contraction of the network. -
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Our goal is to surpass the performance of the Matching Pursuit and Best Basis algorithms and provide progressive time-frequency analysis.
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