Neural networks and fuzzy systems

Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed.

This book is devoted to the new standards, technologies, and communication systems for Artificial Intelligence of Things (AIoT) networks.

This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.

This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.

This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.

This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.

This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes.

This book is an all-inclusive resource that provides a solid foundation on Generative Adversarial Networks (GAN) methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts.

Explore the inner workings of AI along with its limitations and future developments and create your first transparent and trustworthy neuro-symbolic AI systemPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesUnderstand symbolic and statistical techniques through examples and detailed explanationsExplore the potential of neuro-symbolic AI for future developments using case studiesDiscover the benefits of combining symbolic AI with modern neural networks to build transparent and high-performance AI solutionsBook DescriptionNeuro-symbolic AI offers the potential to create intelligent systems that possess both the reasoning capabilities of symbolic AI along with the learning capabilities of neural networks.

Artificial Intelligence and Ethics is a general and wide-ranging survey of the benefits and ethical dilemmas of artificial intelligence (AI).

This book provides a starting point for software professionals to apply artificial neural networks for software reliability prediction without having analyst capability and expertise in various ANN architectures and their optimization.

This book provides a starting point for software professionals to apply artificial neural networks for software reliability prediction without having analyst capability and expertise in various ANN architectures and their optimization.

A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods.

A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods.

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics.

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics.

This comprehensive guide addresses key challenges at the intersection of data science, graph learning, and privacy preservation.

Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems.

A comprehensive text on foundations and techniques of graph neural networks with applications in NLP, data mining, vision and healthcare.

Modern introduction to machine learning with neural networks.

This book presents a comprehensive study of different tools and techniques available to perform network forensics.

Develop your NLP skills from scratch, with an open source toolbox of Python packages, Transformers, Hugging Face, vector databases, and your own Large Language Models.

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning.

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning.

Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error.

Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error.

Our book, Future of Tech Startups and Innovations in the Age of AI, mainly focuses on artificial intelligence (AI) tools, AI-based startups, AI-enabled innovations, Autonomous AI Agents (Auto-GPT), AI-based marketing startups, machine learning for organizations, AI-internet of things (IoT) for new tech companies, AI-enabled drones for agriculture industry, machine learning (ML)/deep learning (DL)-based drip farming, AI-based driverless cars, AI-based weather prediction startups, AI tools for personal branding, AI-based teaching, AI-based doctor/hospital startups, AI for game companies, AI-based finance tools, AI for human resource management, AI-powered management tools, AI tools for future pandemics, AI/ML-based transportation companies, AI for media, AI for carrier counseling, AI for customer care, AI for next generation businesses, and many more applications.

A diverse selection of data science topics explored through a mathematical lens.

Amidst the rampant use of algorithmization enabled by AI, the common theme of AI systems is the human factor.

Amidst the rampant use of algorithmization enabled by AI, the common theme of AI systems is the human factor.

The rise in living standards increases the expectation of people in almost every field.

The rise in living standards increases the expectation of people in almost every field.

Algebraic Structures in Natural Language addresses a central problem in cognitive science concerning the learning procedures through which humans acquire and represent natural language.

Algebraic Structures in Natural Language addresses a central problem in cognitive science concerning the learning procedures through which humans acquire and represent natural language.

Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures introduces AI-based Lagrange optimization techniques that can enable more rational engineering decisions for concrete structures while conforming to codes of practice.

Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures introduces AI-based Lagrange optimization techniques that can enable more rational engineering decisions for concrete structures while conforming to codes of practice.

This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications.

This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications.

The next big area within the information and communication technology field is Artificial Intelligence (AI).

The next big area within the information and communication technology field is Artificial Intelligence (AI).

This book helps to enhance the application of fuzzy logic optimization in the areas of science and engineering.

This book helps to enhance the application of fuzzy logic optimization in the areas of science and engineering.

This book aims to teach the core concepts that make Self-driving vehicles (SDVs) possible.

This book aims to teach the core concepts that make Self-driving vehicles (SDVs) possible.

Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing.

Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing.

Written in accessible language without mathematical formulas, this short book provides an overview of the wide and varied applications of artificial intelligence (AI) across the spectrum of physical sciences.

Written in accessible language without mathematical formulas, this short book provides an overview of the wide and varied applications of artificial intelligence (AI) across the spectrum of physical sciences.

Entropy Randomization in Machine Learning presents a new approach to machine learning-entropy randomization-to obtain optimal solutions under uncertainty (uncertain data and models of the objects under study).

Entropy Randomization in Machine Learning presents a new approach to machine learning-entropy randomization-to obtain optimal solutions under uncertainty (uncertain data and models of the objects under study).