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Knowledge-Based Neurocomputing
Knowledge-Based Neurocomputing
Neurocomputing methods are loosely based on a model of the brain as a network of simple interconnected processing elements corresponding to neurons. These methods derive their power from the collective processing of artificial neurons, the chief advantage being that such systems can learn and adapt to a changing environment. In knowledge-based...
Natural Computing: 4th International Workshop on Natural Computing
Natural Computing: 4th International Workshop on Natural Computing

The complex behavior of systems in nature is rooted in intricate mechanisms of interaction that often supersede human-made systems in terms of reliability, power efficiency, and computational capacity. Researchers have begun to realize that natural systems are a great source of inspiration for novel algorithms in computation and communication...

Neural Networks with Discontinuous/Impact Activations (Nonlinear Systems and Complexity)
Neural Networks with Discontinuous/Impact Activations (Nonlinear Systems and Complexity)

This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural...

Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering (Water Science and Technology Library)
Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering (Water Science and Technology Library)

“Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering” provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important...

JMP 12 Specialized Models
JMP 12 Specialized Models

JMP 12 Specialized Models provides details about modeling techniques such as partitioning, neural networks, nonlinear regression, and time series analysis. Topics include the Gaussian platform, which is useful in analyzing computer simulation experiments. The book also covers the Response Screening platform, which is useful in testing the...

Novel Therapeutic Targets for Antiarrhythmic Drugs
Novel Therapeutic Targets for Antiarrhythmic Drugs

Profiles potential treatment approaches for cardiac arrhythmias

Cardiac arrhythmias of ventricular origin are responsible for the deaths of nearly half a million Americans each year while atrial fibrillation accounts for about 2.3 million cases per year, a rate that is projected to increase 2.5 fold over the next half...

Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python
Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python

Develop real-world applications powered by the latest advances in intelligent systems

Key Features

  • Gain real-world contextualization using deep learning problems concerning research and application
  • Get to know the best practices to improve and optimize your machine...
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Graphics in this book are printed in black and white.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data....

The Neural Simulation Language: A System for Brain Modeling
The Neural Simulation Language: A System for Brain Modeling
The Neural Simulation Language (NSL), developed by Alfredo Weitzenfeld, Michael Arbib, and Amanda Alexander, provides a simulation environment for modular brain modeling. NSL is an object-oriented language offering object-oriented protocols applicable to all levels of neural simulation. One of NSL's main strengths is that it allows for realistic...
An Introduction to 3D Computer Vision Techniques and Algorithms
An Introduction to 3D Computer Vision Techniques and Algorithms

Computer vision encompasses the construction of integrated vision systems and the application of vision to problems of real-world importance. The process of creating 3D models is still rather difficult, requiring mechanical measurement of the camera positions or manual alignment of partial 3D views of a scene. However using algorithms, it is...

Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)
Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)

In the early days of pattern recognition and statistical data analysis life was rather simple: datasets were relatively small, collected from well-designed experiments, analyzed using a few methods that had good theoretical background. Explosive growth of the use of computers led to the creation of huge amounts of data of all kinds,...

Stem Cells and Cancer Stem Cells, Vol. 1: Therapeutic Applications in Disease and Injury
Stem Cells and Cancer Stem Cells, Vol. 1: Therapeutic Applications in Disease and Injury

Difference between tissue specific stem cells and embryonic stem cells is explained. The advantages of the latter are included. The application of human pluripotent stem cells, mesenchymal stem cells, and hematopoietic stem cells in cancer therapy and tissue/organ regeneration is detailed. Role of neural cancer stem cells in brain tumors,...

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