EVENT-DRIVEN UNIVERSAL NEURAL NETWORK CIRCUIT
First Claim
1. :
- A method comprising;
performing event-driven spiking computation in a neural network circuit comprising a plurality of neural modules, wherein each neural module includes multiple digital neurons, each neuron in each neural module is connected to a corresponding neuron in an other neural module via a synapse of an interconnect network of synapses, and the synapse has a learning rule associating the neuron in the neural module with the corresponding neuron in the other neural module;
wherein the event-driven spiking computation comprises;
generating signals that define a set of time steps for event-driven operation of each neuron and event communication via the interconnect network of synapses; and
at each time step, for each neuron, updating an operational state of the neuron and, based on the operational state, determining whether to generate an outgoing firing event in response to receiving an incoming firing event as an input signal from a corresponding neuron in an other neural module via a synapse connecting the neuron to the corresponding neuron, wherein the input signal is weighted by a synaptic weight of the synapse.
0 Assignments
0 Petitions
Accused Products
Abstract
The present invention provides an event-driven universal neural network circuit. The circuit comprises a plurality of neural modules. Each neural module comprises multiple digital neurons such that each neuron in a neural module has a corresponding neuron in another neural module. An interconnection network comprising a plurality of digital synapses interconnects the neural modules. Each synapse interconnects a first neural module to a second neural module by interconnecting a neuron in the first neural module to a corresponding neuron in the second neural module. Corresponding neurons in the first neural module and the second neural module communicate via the synapses. Each synapse comprises a learning rule associating a neuron in the first neural module with a corresponding neuron in the second neural module. A control module generates signals which define a set of time steps for event-driven operation of the neurons and event communication via the interconnection network.
-
Citations
15 Claims
-
1. :
- A method comprising;
performing event-driven spiking computation in a neural network circuit comprising a plurality of neural modules, wherein each neural module includes multiple digital neurons, each neuron in each neural module is connected to a corresponding neuron in an other neural module via a synapse of an interconnect network of synapses, and the synapse has a learning rule associating the neuron in the neural module with the corresponding neuron in the other neural module; wherein the event-driven spiking computation comprises; generating signals that define a set of time steps for event-driven operation of each neuron and event communication via the interconnect network of synapses; and at each time step, for each neuron, updating an operational state of the neuron and, based on the operational state, determining whether to generate an outgoing firing event in response to receiving an incoming firing event as an input signal from a corresponding neuron in an other neural module via a synapse connecting the neuron to the corresponding neuron, wherein the input signal is weighted by a synaptic weight of the synapse. - View Dependent Claims (2, 3, 4, 5)
- A method comprising;
-
6. :
- A system comprising a computer processor, a computer-readable hardware storage device, and program code embodied with the computer-readable hardware storage device for execution by the computer processor to implement a method comprising;
performing event-driven spiking computation in a neural network circuit comprising a plurality of neural modules, wherein each neural module includes multiple digital neurons, each neuron in each neural module is connected to a corresponding neuron in an other neural module via a synapse of an interconnect network of synapses, and the synapse has a learning rule associating the neuron in the neural module with the corresponding neuron in the other neural module; wherein the event-driven spiking computation comprises; generating signals that define a set of time steps for event-driven operation of each neuron and event communication via the interconnect network of synapses; and at each time step, for each neuron, updating an operational state of the neuron and, based on the operational state, determining whether to generate an outgoing firing event in response to receiving an incoming firing event as an input signal from a corresponding neuron in an other neural module via a synapse connecting the neuron to the corresponding neuron, wherein the input signal is weighted by a synaptic weight of the synapse. - View Dependent Claims (7, 8, 9, 10)
- A system comprising a computer processor, a computer-readable hardware storage device, and program code embodied with the computer-readable hardware storage device for execution by the computer processor to implement a method comprising;
-
11. :
- A computer program product comprising a computer-readable hardware storage device having program code embodied therewith, the program code being executable by a computer to implement a method comprising;
performing event-driven spiking computation in a neural network circuit comprising a plurality of neural modules, wherein each neural module includes multiple digital neurons, each neuron in each neural module is connected to a corresponding neuron in an other neural module via a synapse of an interconnect network of synapses, and the synapse has a learning rule associating the neuron in the neural module with the corresponding neuron in the other neural module; wherein the event-driven spiking computation comprises; generating signals that define a set of time steps for event-driven operation of each neuron and event communication via the interconnect network of synapses; and at each time step, for each neuron, updating an operational state of the neuron and, based on the operational state, determining whether to generate an outgoing firing event in response to receiving an incoming firing event as an input signal from a corresponding neuron in an other neural module via a synapse connecting the neuron to the corresponding neuron, wherein the input signal is weighted by a synaptic weight of the synapse. - View Dependent Claims (12, 13, 14, 15)
- A computer program product comprising a computer-readable hardware storage device having program code embodied therewith, the program code being executable by a computer to implement a method comprising;
Specification