In this work, we apply quantum cellular automata (QCA) to study pattern formation and image processing in quantum-diffusion Schrödinger metamedia with generalized complex diffusion coefficients. Generalized complex numbers have the real part and imaginary part with the imaginary unit i2=-1 (classical case), i2=-1 (double numbers) and i2=-0 (dual numbers). They form three 2-D complex algebras. Discretization of the Schrödinger equation gives the quantum Schrödinger cellular automaton with various complex-valued physical parameters. The process of excitation in these media is described by the Schrödinger equations with the wave functions that have values in algebras of the generalized complex numbers. This medium can be used for creation of t...
International audienceOne can think of some physical evolutions as being the emergent-effective resu...
This thesis presents a model of Quantum Cellular Automata (QCA). The presented formalism is a natura...
Face recognition is one of the most ubiquitous examples of pattern recognition in machine learning, ...
In this work, we apply quantum cellular automata (QCA) to study pattern formation and image processi...
In this work, we use quantum color cellular automata to study pattern formation and image processing...
In this paper, the authors present a new approach for image processing based on reverse emergence an...
A cellular automaton that includes some principles from quantum theory is considered. The automaton ...
In this paper we present a systematic view of Quantum Cellular Automata (QCA), a mathematical formal...
In this paper we present a systematic view of Quantum Cellular Automata (QCA), a mathematical formal...
A cellular automaton that includes some principles from quantum theory is considered. The automaton ...
Cellular automata provide a means of obtaining complex behaviour from a simple array of cells and a ...
Quantum cellular automata (QCA) evolve qubits in a quantum circuit depending only on the states of t...
The thesis deals with quantum cellular automata (QCAs) and Fermionic quantum cellular automata (FQCA...
In this paper we introduce a new quantum computation model, the linear quantum cellular automaton. W...
Central to the field of quantum machine learning is the design of quantum perceptrons and neural net...
International audienceOne can think of some physical evolutions as being the emergent-effective resu...
This thesis presents a model of Quantum Cellular Automata (QCA). The presented formalism is a natura...
Face recognition is one of the most ubiquitous examples of pattern recognition in machine learning, ...
In this work, we apply quantum cellular automata (QCA) to study pattern formation and image processi...
In this work, we use quantum color cellular automata to study pattern formation and image processing...
In this paper, the authors present a new approach for image processing based on reverse emergence an...
A cellular automaton that includes some principles from quantum theory is considered. The automaton ...
In this paper we present a systematic view of Quantum Cellular Automata (QCA), a mathematical formal...
In this paper we present a systematic view of Quantum Cellular Automata (QCA), a mathematical formal...
A cellular automaton that includes some principles from quantum theory is considered. The automaton ...
Cellular automata provide a means of obtaining complex behaviour from a simple array of cells and a ...
Quantum cellular automata (QCA) evolve qubits in a quantum circuit depending only on the states of t...
The thesis deals with quantum cellular automata (QCAs) and Fermionic quantum cellular automata (FQCA...
In this paper we introduce a new quantum computation model, the linear quantum cellular automaton. W...
Central to the field of quantum machine learning is the design of quantum perceptrons and neural net...
International audienceOne can think of some physical evolutions as being the emergent-effective resu...
This thesis presents a model of Quantum Cellular Automata (QCA). The presented formalism is a natura...
Face recognition is one of the most ubiquitous examples of pattern recognition in machine learning, ...