Journal ArticleDOI
Quantum learning for neural associative memories
TLDR
Quantum information processing in neural structures results in an exponential increase of patterns storage capacity and can explain the extensive memorization and inferencing capabilities of humans.About:
This article is published in Fuzzy Sets and Systems.The article was published on 2006-07-01. It has received 43 citations till now. The article focuses on the topics: Bidirectional associative memory & Fuzzy associative matrix.read more
Citations
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Journal ArticleDOI
Machine learning & artificial intelligence in the quantum domain: a review of recent progress.
TL;DR: In this article, the authors describe the main ideas, recent developments and progress in a broad spectrum of research investigating ML and AI in the quantum domain, and discuss the fundamental issue of quantum generalizations of learning and AI concepts.
Posted Content
Machine learning \& artificial intelligence in the quantum domain
Vedran Dunjko,Hans J. Briegel +1 more
TL;DR: The main ideas, recent developments and progress are described in a broad spectrum of research investigating ML and AI in the quantum domain, investigating how results and techniques from one field can be used to solve the problems of the other.
Journal ArticleDOI
Applications of quantum inspired computational intelligence: a survey
A. Manju,Madhav J. Nigam +1 more
TL;DR: This paper makes an exhaustive survey of various applications of Quantum inspired computational intelligence (QCI) techniques proposed till date and presents an overview on applications of QCI in solving various problems in engineering.
Journal ArticleDOI
Molecular Processors: From Qubits to Fuzzy Logic
TL;DR: It is demonstrated how it is possible to process different types of logic through molecules, as long as decoherent effects are maintained far away from a pure quantum mechanical system, quantum logic can be processed.
Journal ArticleDOI
Evolving Intelligence in Humans and Machines: Integrative Evolving Connectionist Systems Approach
TL;DR: The paper argues that to understand how the brain operates at its different levels of information processing and then use some of these principles "when building intelligent machines" to achieve a higher level intelligent human behavior.
References
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Book
Neural Networks: A Comprehensive Foundation
TL;DR: Thorough, well-organized, and completely up to date, this book examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.
Book
Quantum Computation and Quantum Information
TL;DR: In this article, the quantum Fourier transform and its application in quantum information theory is discussed, and distance measures for quantum information are defined. And quantum error-correction and entropy and information are discussed.
Journal ArticleDOI
Neural networks and physical systems with emergent collective computational abilities
TL;DR: A model of a system having a large number of simple equivalent components, based on aspects of neurobiology but readily adapted to integrated circuits, produces a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size.
Quantum Computation and Quantum Information
TL;DR: This chapter discusses quantum information theory, public-key cryptography and the RSA cryptosystem, and the proof of Lieb's theorem.
Book
neural networks and fuzzy systems a dynamical systems approach to machine intelligence
TL;DR: This work combines neural networks and fuzzy systems, presenting neural networks as trainable dynamical systems and developing mechanisms and principles of adaption, self-organization, convergence and global stability.