Understanding And Bridging The Gap Between Neuromorphic Computing And Machine Learning

Quality Electronic Design (QED)’s landscape spans a vast region where territories of many participating disciplines and technologies overlap. This book explores the latest trends in several key topics related to quality electronic design, with emphasis on Hardware Security, Cybersecurity, Machine Learning, and application of Artificial Intelligence (AI). The book includes topics in nonvolatile memories (NVM), Internet of Things (IoT), FPGA, and Neural Networks.

The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields. Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals.

Artificial neural networks, concept, application and types / M. Khishe and Gh. R. Parvizi, Department of Electronic Engineering, Imam Khomeini University of Naval Science, Nowshahr, Iran, and others -- Emotion recognition from facial expressions using artificial neural networks : A review / Sibel Senan, Zeynep Orman and Fulya Akcan, Department of Computer Engineering, Istanbul University-Cerrahpasa, Istanbul, Turkey -- Dipole mode index prediction with artificial neural networks / Kalpesh R. Patil and Masaaki Iiyama, Post-Doctorate Research Scholar, Academic Center for Computing and Media Studies, Kyoto University, Kyoto, Japan, and others.

COGNITIVE ANALYTICS AND REINFORCEMENT LEARNING The combination of cognitive analytics and reinforcement learning is a transformational force in the field of modern technological breakthroughs, reshaping the decision-making, problem-solving, and innovation landscape; this book offers an examination of the profound overlap between these two fields and illuminates its significant consequences for business, academia, and research. Cognitive analytics and reinforcement learning are pivotal branches of artificial intelligence. They have garnered increased attention in the research field and industry domain on how humans perceive, interpret, and respond to information. Cognitive science allows us to understand data, mimic human cognitive processes, and make informed decisions to identify patterns and adapt to dynamic situations. The process enhances the capabilities of various applications. Readers will uncover the latest advancements in AI and machine learning, gaining valuable insights into how these technologies are revolutionizing various industries, including transforming healthcare by enabling smarter diagnosis and treatment decisions, enhancing the efficiency of smart cities through dynamic decision control, optimizing debt collection strategies, predicting optimal moves in complex scenarios like chess, and much more. With a focus on bridging the gap between theory and practice, this book serves as an invaluable resource for researchers and industry professionals seeking to leverage cognitive analytics and reinforcement learning to drive innovation and solve complex problems. The book’s real strength lies in bridging the gap between theoretical knowledge and practical implementation. It offers a rich tapestry of use cases and examples. Whether you are a student looking to gain a deeper understanding of these cutting-edge technologies, an AI practitioner seeking innovative solutions for your projects, or an industry leader interested in the strategic applications of AI, this book offers a treasure trove of insights and knowledge to help you navigate the complex and exciting world of cognitive analytics and reinforcement learning. Audience The book caters to a diverse audience that spans academic researchers, AI practitioners, data scientists, industry leaders, tech enthusiasts, and educators who associate with artificial intelligence, data analytics, and cognitive sciences.

Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making Edited by high-level academics and researchers in intelligent systems and neural networks Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks

Would you achieve more if you could envision your success? A neural network is a computing ѕуѕtеm made uр оf a numbеr of ѕimрlе, highlу intеrсоnnесtеd рrосеѕѕing elements, which рrосеѕѕ infоrmаtiоn bу thеir dуnаmiс ѕtаtе response to еxtеrnаl inputs. All of this sounds fancy, but what does it mean for computer intelligence, or for the future? In this book, you will find answers to many practical and theoretical questions related to neural networks, from insights about nodes and hidden layers to error spaces, network analyses, and computing influences. Topics will be discussed, such as: What the definition of neural networks encompasses and what all the elements pertaining to them mean. The main advantages of neural networks and how to leverage and apply them. Limitations to neural networks. How neural networks differ from conventional computing systems. Neural Network applications for medical diagnostics, smart computers, artificial intelligence, and forex or stock trading. Troubleshooting tips for when neural networks stop functioning. If you are even in the least interested in computer technology, artificial intelligence, or what the technological future will bring, you need to read this book and get a better understanding of neural networks and their many applications. This book will bring you to the core of how they function and what you can do with them. Add this book to your cart.