Neuronal network structure and method to operate a neuronal network structure
AssigneeCodebox Computerdienste GmbH
InventorsJochen Mersmann, Victor Jirsa
Life of this patent
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Abstract
A neuronal network structure including a plurality of automata interconnected one with each other through synaptic links forming a connectivity matrix. The neural network structure acts as a machine that can be operated such that the machine shows different behaviours including periodic and non-periodic patterns, multistable patterns and more complex patterns such as spirals. A method to operate a neuronal network structure.
Claims19
A neuronal network structure, comprising
- a processing unit;
- an input unit for inputting variables into the processing unit;
- and
- an output unit for outputting processed variables from the processing unit;
- wherein the processing unit comprises a plurality of automata interconnected one with each other by means of interconnections forming a connectivity matrix, with
- each of said automata having the same time-continuous dynamics in absence of interconnections prescribed by a typically nonlinear function composed of a product of the automaton's state variable and another nonlinear function of the automaton's state variable;
- each of said interconnections being dependent on state variables, whereas the deviations from identical interconnections across all automata are small;
- the neuronal network structure further having a process-based architecture, a process-based architecture meaning that the processing unit generates a low-dimensional time-continuous dynamics described as the process, said process being the set of all lawful behaviors of a given phase flow on a manifold.
A neuronal network structure comprising a processing unit, an input unit for inputting variables into the processing unit, and an output unit for outputting processed variables from the processing unit, wherein the processing unit comprises a plurality of automata interconnected one with each other by means of identical interconnections forming a connectivity matrix, and wherein the neuronal network structure has a process-based architecture.
A neuronal network structure composed of a network of automata interconnected by synaptic links, the neuronal network structure comprising nodes forming the network, said nodes being said automata equivalent to neuronal populations, said synaptic links being connections between said automata;
- wherein the dynamics of said network automata are defined by time-continuous dynamic systems and a process is determined by the entirety of the temporal behaviours of said network nodes or automata which may have an arbitrarily large complexity, thus forming a cognitive architecture.
A method to operate a neuronal network structure with a plurality of automata interconnected one with each other by means of identical interconnections forming a connectivity matrix, the operation being process-based.
A method of operating a neuronal network, comprising
- inputting, by an input unit of the neuronal network, variables into a processing unit of the neuronal network, the processing unit comprising a plurality of automata interconnected one with each other by interconnections forming a connectivity matrix;
- generating, by the processing unit, low-dimensional time-continuous dynamics described as a process, said process being a set of all lawful behaviors of a given phase flow on a manifold;
- outputting, by an output unit of the neuronal network, processed variables from the processing unit;
- and
- controlling movement of a machine based on the processed variables output from the processing unit.
Dependencies are inferred from the claim text.