### A Compendium of Solid State Theory

Category: E-Book

**A Compendium of Solid State Theory by Ladislaus Alexander BĂˇnyai**

English | PDF,EPUB | 2018 | 158 Pages | ISBN : 3319786121 | 5.4 MB

Designed to sit alongside more conventional established condensed matter physics textbooks, this compact volume offers a concise presentation of the principles of solid state theory, ideal for advanced students and researchers requiring an overview or a quick refresher on a specific topic.

**Evolutionary Algorithms and Neural Networks: Theory and Applications by Seyedali Mirjalili**

English | PDF,EPUB | 2018 (2019 Edition) | 164 Pages | ISBN : 3319930249 | 12.28 MB

This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.

### Theory and Simulation of Random Phenomena Mathematical Foundations and Physical Applications

Category: E-Book

**Theory and Simulation of Random Phenomena: Mathematical Foundations and Physical Applications by Ettore Vitali**

English | PDF,EPUB | 2018 | 245 Pages | ISBN : 3319905147 | 7 MB

The purpose of this book is twofold: first, it sets out to equip the reader with a sound understanding of the foundations of probability theory and stochastic processes, offering step-by-step guidance from basic probability theory to advanced topics, such as stochastic differential equations, which typically are presented in textbooks that require a very strong mathematical background. Second, while leading the reader on this journey, it aims to impart the knowledge needed in order to develop algorithms that simulate realistic physical systems.