Quantum-like Networks: An Approach To Neural Behavior Through Their Mathematics And Logic PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Quantum-like Networks: An Approach To Neural Behavior Through Their Mathematics And Logic PDF full book. Access full book title Quantum-like Networks: An Approach To Neural Behavior Through Their Mathematics And Logic by Stephen A Selesnick. Download full books in PDF and EPUB format.
Author: Stephen A Selesnick
Publisher: World Scientific
ISBN: 9811260710
Category : Science
Languages : en
Pages : 354
Get Book Here
Book Description
Do brains compute? If they do, what do they compute and how do they do it? The first part of the book introduces the development of a model that simulates actual biological neurons more closely than do current standard models of neural networks, as well as the deduction of its physics-like and computational properties from first principles. The second part presents a collection of applications of the model to memory formation and loss, a general syntax for memory retrieval, language itself, and certain forms of aphasia. A linear development of the discussion with proofs in situ is employed by the author, making the book essentially self-contained. A pair of helpful appendices are provided to acquaint the reader with necessary fundamentals of topics in logic and mathematics. Quantum-like Networks: An Approach to Neural Behavior through their Mathematics and Logic will show you an entirely new approach to an ancient subject.
Author: Stephen A Selesnick
Publisher: World Scientific
ISBN: 9811260710
Category : Science
Languages : en
Pages : 354
Get Book Here
Book Description
Do brains compute? If they do, what do they compute and how do they do it? The first part of the book introduces the development of a model that simulates actual biological neurons more closely than do current standard models of neural networks, as well as the deduction of its physics-like and computational properties from first principles. The second part presents a collection of applications of the model to memory formation and loss, a general syntax for memory retrieval, language itself, and certain forms of aphasia. A linear development of the discussion with proofs in situ is employed by the author, making the book essentially self-contained. A pair of helpful appendices are provided to acquaint the reader with necessary fundamentals of topics in logic and mathematics. Quantum-like Networks: An Approach to Neural Behavior through their Mathematics and Logic will show you an entirely new approach to an ancient subject.
Author: Stefanie Czischek
Publisher: Springer Nature
ISBN: 3030527158
Category : Science
Languages : en
Pages : 205
Get Book Here
Book Description
Quantum systems with many degrees of freedom are inherently difficult to describe and simulate quantitatively. The space of possible states is, in general, exponentially large in the number of degrees of freedom such as the number of particles it contains. Standard digital high-performance computing is generally too weak to capture all the necessary details, such that alternative quantum simulation devices have been proposed as a solution. Artificial neural networks, with their high non-local connectivity between the neuron degrees of freedom, may soon gain importance in simulating static and dynamical behavior of quantum systems. Particularly promising candidates are neuromorphic realizations based on analog electronic circuits which are being developed to capture, e.g., the functioning of biologically relevant networks. In turn, such neuromorphic systems may be used to measure and control real quantum many-body systems online. This thesis lays an important foundation for the realization of quantum simulations by means of neuromorphic hardware, for using quantum physics as an input to classical neural nets and, in turn, for using network results to be fed back to quantum systems. The necessary foundations on both sides, quantum physics and artificial neural networks, are described, providing a valuable reference for researchers from these different communities who need to understand the foundations of both.
Author: Jerome R. Busemeyer
Publisher: Cambridge University Press
ISBN: 110701199X
Category : Business & Economics
Languages : en
Pages : 425
Get Book Here
Book Description
Introduces principles drawn from quantum theory to present a new framework for modeling human cognition and decision.
Author: Karl H. Pribram
Publisher: Psychology Press
ISBN: 1317780949
Category : Psychology
Languages : en
Pages : 566
Get Book Here
Book Description
The result of the first Appalachian Conference on neurodynamics, this volume focuses on processing in biological neural networks. How do brain processes become organized during decision making? That is, what are the neural antecedents that determine which course of action is to be pursued? Half of the contributions deal with modelling synapto-dendritic and neural ultrastructural processes; the remainder, with laboratory research findings, often cast in terms of the models. The interchanges at the conference and the ensuing publication also provide a foundation for further meetings. These will address how processes in different brain systems, coactive with the neural residues of experience and with sensory input, determine decisions.
Author:
Publisher: Psychology Press
ISBN: 9780805817454
Category : Artificial intelligence
Languages : en
Pages : 916
Get Book Here
Book Description
Author: Paul Werbos
Publisher: Routledge
ISBN: 1317713419
Category : Psychology
Languages : en
Pages : 916
Get Book Here
Book Description
Centered around 20 major topic areas of both theoretical and practical importance, the World Congress on Neural Networks provides its registrants -- from a diverse background encompassing industry, academia, and government -- with the latest research and applications in the neural network field.
Author: Nam H. Nguyen
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 225
Get Book Here
Book Description
Quantum computing is becoming a reality, at least on a small scale. However, designing a good quantum algorithm is still a challenging task. This has been a huge major bottleneck in quantum computation for years. In this work, we will show that it is possible to take a detour from the conventional programming approach by incorporating machine learning techniques, speci cally neural networks, to train a quantum system such that the desired algorithm is \learned," thus obviating the program design obstacle. Our work here merges quantum computing and neural networks to form what we call \Quantum Neural Networks" (QNNs). Another serious issue one needs to overcome when doing anything quantum is the problem of \noise and decoherence". A well-known technique to overcome this issue is using error correcting code. However, error correction schemes require an enormous amount of additional ancilla qubits, which is not feasible for the current state-of-the-art quantum computing devices or any near-term devices for that matter. We show in this work that QNNs are robust to noise and decoherence, provide error suppression quantum algorithms. Furthermore, not only are our QNN models robust to noise and decoherehce, we show that they also possess an inherent speed-up, in term of being able to learned a task much faster, over various classical neural networks, at least on the set of problems we benchmarked them on. Afterward, we show that although our QNN model is designed to run on a fundamental level of a quantum system, we can also decompose it into a sequence of gates and implement it on current quantum hardware devices. We did this for a non-trivial problem known as the \entanglement witness" calculation. We then propose a couple of di erent hybrid quantum neural network architectures, networks with both quantum and classical information processing. We hope that this might increase the capability over previous QNN models in terms of the complexity of the problems it might be able to solve.
Author: Sabre Kais
Publisher: Frontiers Media SA
ISBN: 2889715094
Category : Science
Languages : en
Pages : 114
Get Book Here
Book Description
Author: Om Prakash Jena
Publisher: CRC Press
ISBN: 1000600270
Category : Computers
Languages : en
Pages : 206
Get Book Here
Book Description
This book looks at industry change patterns and innovations (such as artificial intelligence, machine learning, big data analysis, and blockchain support and efficiency technology) that are speeding up industrial transformation, industrial infrastructure, biodiversity, and productivity. This book focuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturing. It also offers insights into manufacturing, logistics, and supply chain, where systems have undergone an industrial transformation. It discusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposure. It goes on to cover the effects that the Fourth Industrial Revolution has on industrial infrastructures and looks at the current industry change patterns and innovations that are accelerating industrial transformation activities. Researchers, scholars, and students from different countries will appreciate this book for its real-world applications and knowledge acquisition. This book targets manufacturers, industry owners, product developers, scientists, logistics, and supply chain engineers. Focuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturing Offers insights into manufacturing, logistics, and supply chain where systems have undergone an industrial transformation Discusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposure Covers the effects that the 4th Industrial Revolution has on industrial infrastructures Looks at industry change patterns and innovations that are speeding up industrial transformation activities
Author: Andrzej Jankowski
Publisher: Springer
ISBN: 3319576275
Category : Technology & Engineering
Languages : en
Pages : 663
Get Book Here
Book Description
The book outlines selected projects conducted under the supervision of the author. Moreover, it discusses significant relations between Interactive Granular Computing (IGrC) and numerous dynamically developing scientific domains worldwide, along with features characteristic of the author’s approach to IGrC. The results presented are a continuation and elaboration of various aspects of Wisdom Technology, initiated and developed in cooperation with Professor Andrzej Skowron. Based on the empirical findings from these projects, the author explores the following areas: (a) understanding the causes of the theory and practice gap problem (TPGP) in complex systems engineering (CSE); (b) generalizing computing models of complex adaptive systems (CAS) (in particular, natural computing models) by constructing an interactive granular computing (IGrC) model of networks of interrelated interacting complex granules (c-granules), belonging to a single agent and/or to a group of agents; (c) developing methodologies based on the IGrC model to minimize the negative consequences of the TPGP. The book introduces approaches to the above issues, using the proposed IGrC model. In particular, the IGrC model refers to the key mechanisms used to control the processes related to the implementation of CSE projects. One of the main aims was to develop a mechanism of IGrC control over computations that model a project’s implementation processes to maximize the chances of its success, while at the same time minimizing the emerging risks. In this regard, the IGrC control is usually performed by means of properly selected and enforced (among project participants) project principles. These principles constitute examples of c-granules, expressed by complex vague concepts (represented by c-granules too). The c-granules evolve with time (in particular, the meaning of the concepts is also subject of change). This methodology is illustrated using project principles applied by the author during the implementation of the POLTAX, AlgoTradix, Merix, and Excavio projects outlined in the book.
