Molecular Evolution: A Statistical Approach

Susan J. Karcher - Molecular Biology: A Project Approach  eBooks & eLearning

Posted by rotten comics at Aug. 25, 2016
Susan J. Karcher - Molecular Biology: A Project Approach

Susan J. Karcher - Molecular Biology: A Project Approach
1995 | ISBN: 0123977207 | English | 280 pages | PDF | 12.5 MB
Spacecraft Reliability and Multi-State Failures: A Statistical Approach (repost)

Joseph Homer Saleh, Jean-Fransois Castet, "Spacecraft Reliability and Multi-State Failures: A Statistical Approach"
English | 2011 | ISBN: 0470687916 | 216 pages | PDF | 9,2 MB
Nonlinear Signal Processing: A Statistical Approach (repost)

Nonlinear Signal Processing: A Statistical Approach
by Gonzalo R. Arce
English | 2004 | ISBN: 0471676241 | 484 pages | PDF | 18.04 MB
Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach (Repost)

Rafal Weron, "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach"
English | 2006-12-15 | ISBN: 047005753x | 192 pages | PDF | 2.86 mb
Six Sigma for Organizational Excellence: A Statistical Approach (repost)

Six Sigma for Organizational Excellence: A Statistical Approach by K. Muralidharan
English | 2015 | ISBN-10: 8132223241 | 622 pages | pdf | 11,4 mb
A Statistical Approach to Neural Networks for Pattern Recognition by Robert A. Dunn [Repost]

A Statistical Approach to Neural Networks for Pattern Recognition by Robert A. Dunne
English | July 16, 2007 | ISBN: 0471741086 | 288 Pages | PDF | 10 MB

An accessible and up-to-date treatment featuring the connection between neural networks and statistics. A Statistical Approach to Neural Networks for Pattern Recognition presents a statistical treatment of the Multilayer Perceptron (MLP), which is the most widely used of the neural network models.
Adaptive Differential Evolution: A Robust Approach to Multimodal Problem Optimization by Arthur C. Sanderson

Adaptive Differential Evolution: A Robust Approach to Multimodal Problem Optimization (Adaptation, Learning, and Optimization) by Arthur C. Sanderson
English | Sep 2, 2009 | ISBN: 3642015263 | 170 Pages | PDF | 3 MB

The fundamental theme of this book is theoretical study of differential evolution and algorithmic analysis of parameter adaptive schemes. The book offers real-world insights into a variety of large-scale complex industrial applications.
Selfish Sounds and Linguistic Evolution: A Darwinian Approach to Language Change

Selfish Sounds and Linguistic Evolution: A Darwinian Approach to Language Change by Nikolaus Ritt
English | July 5, 2004 | ISBN: 0521826713 | 342 Pages | PDF | 3 MB

This new perspective on language change looks at a number of developments in the history of sounds and words and explains them in terms of Darwin's evolutionary theory. Nikolaus Ritt demonstrates how the constituents of language can be regarded as mental patterns, or "memes", which copy themselves from one brain to another when communication and language acquisition occur. Challenging established models of linguistic competence, Ritt's controversial approach will stimulate debate among evolutionary biologists, cognitive scientists and linguists.
Material Inhomogeneities and their Evolution: A Geometric Approach by Marcelo Epstein

Material Inhomogeneities and their Evolution: A Geometric Approach (Interaction of Mechanics and Mathematics) by Marcelo Epstein
English | Nov 9, 2007 | ISBN: 3540723722 | 275 Pages | PDF | 14 MB

The main goal of this book is to present a new point of view on the theory of material inhomogeneities by means of a strong mathematical tool, namely, differential geometry. …
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) by Kenneth Price [Repost]

Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) by Kenneth Price
English | Dec 22, 2005 | ISBN: 3540209506 | 542 Pages | PDF | 10 MB

Problems demanding globally optimal solutions are ubiquitous, yet many are intractable when they involve constrained functions having many local optima and interacting, mixed-type variables.