Quantum Neural Computation PDF Download
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| Author | : Vladimir G. Ivancevic |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 938 |
| Release | : 2010-01-18 |
| Genre | : Computers |
| ISBN | : 9048133505 |
Download Quantum Neural Computation Book in PDF, ePub and Kindle
Quantum Neural Computation is a graduate–level monographic textbook. It presents a comprehensive introduction, both non-technical and technical, into modern quantum neural computation, the science behind the fiction movie Stealth. Classical computing systems perform classical computations (i.e., Boolean operations, such as AND, OR, NOT gates) using devices that can be described classically (e.g., MOSFETs). On the other hand, quantum computing systems perform classical computations using quantum devices (quantum dots), that is devices that can be described only using quantum mechanics. Any information transfer between such computing systems involves a state measurement. This book describes this information transfer at the edge of classical and quantum chaos and turbulence, where mysterious quantum-mechanical linearity meets even more mysterious brain’s nonlinear complexity, in order to perform a super–high–speed and error–free computations. This monograph describes a crossroad between quantum field theory, brain science and computational intelligence.
| Author | : John A. Hertz |
| Publisher | : CRC Press |
| Total Pages | : 352 |
| Release | : 2018-03-08 |
| Genre | : Science |
| ISBN | : 0429968213 |
Download Introduction To The Theory Of Neural Computation Book in PDF, ePub and Kindle
Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.
| Author | : Melanie Swan |
| Publisher | : World Scientific |
| Total Pages | : 551 |
| Release | : 2022-05-30 |
| Genre | : Computers |
| ISBN | : 1800610637 |
Download Quantum Computing For The Brain Book in PDF, ePub and Kindle
Quantum Computing for the Brain argues that the brain is the killer application for quantum computing. No other system is as complex, as multidimensional in time and space, as dynamic, as less well-understood, as of peak interest, and as in need of three-dimensional modeling as it functions in real-life, as the brain.Quantum computing has emerged as a platform suited to contemporary data processing needs, surpassing classical computing and supercomputing. This book shows how quantum computing's increased capacity to model classical data with quantum states and the ability to run more complex permutations of problems can be employed in neuroscience applications such as neural signaling and synaptic integration. State-of-the-art methods are discussed such as quantum machine learning, tensor networks, Born machines, quantum kernel learning, wavelet transforms, Rydberg atom arrays, ion traps, boson sampling, graph-theoretic models, quantum optical machine learning, neuromorphic architectures, spiking neural networks, quantum teleportation, and quantum walks.Quantum Computing for the Brain is a comprehensive one-stop resource for an improved understanding of the converging research frontiers of foundational physics, information theory, and neuroscience in the context of quantum computing.
| Author | : Alexandr A. Ezhov |
| Publisher | : |
| Total Pages | : 248 |
| Release | : 2003 |
| Genre | : Neural networks (Computer science) |
| ISBN | : |
Download Introduction to Quantum Neural Technologies Book in PDF, ePub and Kindle
This is a first introductory book in Quantum Neural Technology -- a new and promising area of informatics. Combination of the ideas from quantum computing and neural computing raises the possibility of dramatically decreasing the complexity of neural systems by replacing networks of classical neurons with a single quantum neuron. In the first two chapters, the fundamentals of neural technologies and of quantum computing are presented. In the third chapter, it is outlined how the problems typical for classical neural technology can be solved by using quantum neural technology. This book is very useful to students, teachers, researchers, and engineers, who are working in informatics or just interested in being briefly aware of it.
| Author | : Geoffrey Hinton |
| Publisher | : MIT Press |
| Total Pages | : 420 |
| Release | : 1999-05-24 |
| Genre | : Medical |
| ISBN | : 9780262581684 |
Download Unsupervised Learning Book in PDF, ePub and Kindle
Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.
| Author | : Maria Schuld |
| Publisher | : Springer Nature |
| Total Pages | : 321 |
| Release | : 2021-10-17 |
| Genre | : Science |
| ISBN | : 3030830985 |
Download Machine Learning with Quantum Computers Book in PDF, ePub and Kindle
This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.
| Author | : Nikola Kasabov |
| Publisher | : Physica |
| Total Pages | : 411 |
| Release | : 2013-11-11 |
| Genre | : Computers |
| ISBN | : 3790818569 |
Download Future Directions for Intelligent Systems and Information Sciences Book in PDF, ePub and Kindle
This edited volume comprises invited chapters that cover five areas of the current and the future development of intelligent systems and information sciences. Half of the chapters were presented as invited talks at the Workshop "Future Directions for Intelligent Systems and Information Sciences" held in Dunedin, New Zealand, 22-23 November 1999 after the International Conference on Neuro-Information Processing (lCONIPI ANZIISI ANNES '99) held in Perth, Australia. In order to make this volume useful for researchers and academics in the broad area of information sciences I invited prominent researchers to submit materials and present their view about future paradigms, future trends and directions. Part I contains chapters on adaptive, evolving, learning systems. These are systems that learn in a life-long, on-line mode and in a changing environment. The first chapter, written by the editor, presents briefly the paradigm of Evolving Connectionist Systems (ECOS) and some of their applications. The chapter by Sung-Bae Cho presents the paradigms of artificial life and evolutionary programming in the context of several applications (mobile robots, adaptive agents of the WWW). The following three chapters written by R.Duro, J.Santos and J.A.Becerra (chapter 3), GCoghill . (chapter 4), Y.Maeda (chapter 5) introduce new techniques for building adaptive, learning robots.
| Author | : Maria Schuld |
| Publisher | : Springer |
| Total Pages | : 293 |
| Release | : 2018-08-30 |
| Genre | : Science |
| ISBN | : 3319964240 |
Download Supervised Learning with Quantum Computers Book in PDF, ePub and Kindle
Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.
| Author | : Colin P. Williams |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 257 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 146120495X |
Download Ultimate Zero and One Book in PDF, ePub and Kindle
As miniaturisation deepens, and nanotechnology and its machines become more prevalent in the real world, the need to consider using quantum mechanical concepts to perform various tasks in computation increases. Such tasks include: the teleporting of information, breaking heretofore "unbreakable" codes, communicating with messages that betray eavesdropping, and the generation of random numbers. This is the first book to apply quantum physics to the basic operations of a computer, representing the ideal vehicle for explaining the complexities of quantum mechanics to students, researchers and computer engineers, alike, as they prepare to design and create the computing and information delivery systems for the future. Both authors have solid backgrounds in the subject matter at the theoretical and more practical level. While serving as a text for senior/grad level students in computer science/physics/engineering, this book has its primary use as an up-to-date reference work in the emerging interdisciplinary field of quantum computing - the only prerequisite being knowledge of calculus and familiarity with the concept of the Turing machine.
| Author | : Philip D. Wasserman |
| Publisher | : Van Nostrand Reinhold Company |
| Total Pages | : 280 |
| Release | : 1993 |
| Genre | : Computers |
| ISBN | : |
Download Advanced Methods in Neural Computing Book in PDF, ePub and Kindle
This is the engineer's guide to artificial neural networks, the advanced computing innovation which is posed to sweep into the world of business and industry. The author presents the basic principles and advanced concepts by means of high-performance paradigms which function effectively in real-world situations.
