An Introduction to Kalman Filtering With Matlab Examples

Proper Generalized Decompositions: An Introduction to Computer Implementation with Matlab

Proper Generalized Decompositions: An Introduction to Computer Implementation with Matlab By Elías Cueto, David González, Icíar Alfaro
2016 | 108 Pages | ISBN: 331929993X | PDF | 3 MB
Solar PV and Wind Energy Conversion Systems: An Introduction to Theory, Modeling with MATLAB/SIMULINK

S. Sumathi, "Solar PV and Wind Energy Conversion Systems: An Introduction to Theory, Modeling with MATLAB/SIMULINK, and the Role of Soft Computing Techniques"
English | ISBN: 3319149407 | 2015 | 816 pages | PDF | 30 MB

A Brief Introduction to Engineering Computation with MATLAB  eBooks & eLearning

Posted by hill0 at Dec. 5, 2017
A Brief Introduction to Engineering Computation with MATLAB

A Brief Introduction to Engineering Computation with MATLAB by Serhat Beyenir
English | 2016 | ISBN: NA | 166 Pages | PDF | 3.86 MB

An Introduction to Language Processing with Perl and Prolog (Repost)  eBooks & eLearning

Posted by AvaxGenius at Oct. 17, 2017
An Introduction to Language Processing with Perl and Prolog (Repost)

An Introduction to Language Processing with Perl and Prolog: An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German By Pierre M. Nugues
English | PDF | 2006 | 524 Pages | ISBN : 354025031X | 3.46 MB

The areas of natural language processing and computational linguistics have continued to grow in recent years, driven by the demand to automatically process text and spoken data. With the processing power and techniques now available, research is scaling up from lab prototypes to real-world, proven applications.

An Introduction to Statistical Learning: with Applications in R (Repost)  eBooks & eLearning

Posted by insetes at Oct. 17, 2017
An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R By Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
2014 | 426 Pages | ISBN: 1461471370 | PDF | 11 MB

Introduction to Linear Programming with MATLAB  eBooks & eLearning

Posted by interes at Oct. 16, 2017
Introduction to Linear Programming with MATLAB

Introduction to Linear Programming with MATLAB by Shashi Kant Mishra and Bhagwat Ram
English | 2017 | ISBN: 1138092266 | 327 pages | PDF | 2 MB
Fundamentals Of Algebraic Modeling: An Introduction To Mathematical Modeling With Algebra And Statistics [Repost]

Fundamentals Of Algebraic Modeling: An Introduction To Mathematical Modeling With Algebra And Statistics by Daniel Timmons
English | 24 Dec. 2008 | ISBN: 0495555096 | 456 Pages | PDF | 12.32 MB

The fifth edition of "Fundamentals of Algebraic Modeling" strives to show the student connections between math and their daily lives. Algebraic modeling concepts and solutions are presented in non-threatening,
Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises, 4th Edition (repost)

Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises, 4th Edition by Robert Grover Brown, Patrick Y. C. Hwang
English | ISBN: 0470609699 | 2012 | PDF | 400 pages | 4,6 MB
Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises (4th Edition)

Robert Grover Brown, Patrick Y. C. Hwang, "Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises (4th Edition)"
English | ISBN: 0470609699 | 2012 | PDF | 400 pages | 4,6 MB
An Introduction to Mathematical Finance with Applications: Understanding and Building Financial Intuition (Repost)

An Introduction to Mathematical Finance with Applications: Understanding and Building Financial Intuition By Arlie O. Petters, Xiaoying Dong
English | EPUB | 2016 | 483 Pages | ISBN : 1493937812 | 6 MB

This textbook aims to fill the gap between those that offer a theoretical treatment without many applications and those that present and apply formulas without appropriately deriving them. The balance achieved will give readers a fundamental understanding of key financial ideas and tools that form the basis for building realistic models, including those that may become proprietary.