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Static and Dynamic Neural Networks: From Fundamentals to Advanced Theory

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With the evolution of our complex technological society and the introduction of new notions and innovative theoretical tools in the field of intelligent systems, the field of neural networks is undergoing an enormous evolution. These evolving and innovative theoretical tools are centered around the theory of soft computing, a theory that embodies the theory from the fields of neural networks, fuzzy logic, evolutionary computing, probabilistic computing, and genetic algorithms. These tools of soft computing are providing some intelligence and robustness in the complex and uncertain systems similar to those seen in natural biological species.

Intelligence — the ability to learn, understand, and adapt — is the creation of nature, and it plays a key role in human actions and in the actions of many other biological species. Humans possess some robust attributes of learning and adaptation, and that's what makes them so intelligent. We humans react through the process of learning and adaptation on the information received through a widely distributed network of sensors and control mechanisms in our bodies. The faculty of cognition — which is found in our carbon-based computer, the brain — acquires information about the environment through various natural sensory mechanisms such as vision, hearing, touch, taste, and smell.
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Harmony Search Algorithm: Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) (Advances in Intelligent Systems and Computing)
Harmony Search Algorithm: Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) (Advances in Intelligent Systems and Computing)

This book presents state-of-the-art technical contributions based around one of the most successful evolutionary optimization algorithms published to date: Harmony Search. Contributions span from novel technical derivations of this algorithm to applications in the broad fields of civil engineering, energy, transportation &...

Sampling Algorithms (Springer Series in Statistics)
Sampling Algorithms (Springer Series in Statistics)
This book is based upon courses on sampling algorithms. After having used scattered notes for several years, I have decided to completely rewrite the material in a consistent way. The books of Brewer and Hanif (1983) and H´ajek (1981) have been my works of reference. Brewer and Hanif (1983) have drawn up an...
Computational Physics: Problem Solving with Python
Computational Physics: Problem Solving with Python
The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming.

This upper-division text provides an
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Java Data Science Cookbook
Java Data Science Cookbook

Key Features

  • This book provides modern recipes in small steps to help an apprentice cook become a master chef in data science
  • Use these recipes to obtain, clean, analyze, and learn from your data
  • Learn how to get your data science applications to production and enterprise...
Data Mining and Statistics for Decision Making
Data Mining and Statistics for Decision Making
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify...
Big Data Visualization
Big Data Visualization
Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization About This Book This unique guide teaches you how to visualize your cluttered, huge amounts of big data with ease It is rich with ample options and solid use cases for big data visualization, and is a must-have book...
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