Abstract:
A network device may receive an activation instruction. The network device may provide network resources. The activation instruction may request the network device to activate a particular network resource that is deactivated. The activation instruction may be associated with a license that identifies the particular network resource and identifies a resource request of a user. The network device may configure, based on the activation instruction, a component of the network device to activate the particular network resource. The component, after being configured to activate the particular network resource, may allow data flows, received by the network device, to be provided towards a destination device using the particular network resource. The network device may receive a data flow and provide, by the component of the network device, the data flow towards the destination device using the particular network resource.
Abstract:
A mobile device and a server exchange information in response to the mobile device detecting a proximity beacon. Upon detecting the proximity beacon, the mobile device initiates a web service call to the server. A mobile device user will indicate a choice whether to opt-in upon registration. If the user has opted in, the server will retrieve additional information about the user including prescription information. The server will transmit prescription information and other marketing information to the mobile device. The server may be configured to receive additional information from the mobile device, for example, a request for a prescription to be refilled.
Abstract:
A system may receive first user input that identifies an optical route in an optical network, may receive a second user input that identifies a view type, and may provide, based on the first user input and the second user input, a user interface. The user interface may display, based on the identified view type, a representation of components associated with the optical route, a representation of ports on each of the components, a representation of a first parameter associated with each port, and a representation of an optical link associated with the optical route, where the representation of the optical link identifies a port on each of the components that connects the optical link to each of the components.
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.
Abstract:
Embodiments of the invention provide a neural network comprising multiple functional neural core circuits, and a dynamically reconfigurable switch interconnect between the functional neural core circuits. The interconnect comprises multiple connectivity neural core circuits. Each functional neural core circuit comprises a first and a second core module. Each core module comprises a plurality of electronic neurons, a plurality of incoming electronic axons, and multiple electronic synapses interconnecting the incoming axons to the neurons. Each neuron has a corresponding outgoing electronic axon. In one embodiment, zero or more sets of connectivity neural core circuits interconnect outgoing axons in a functional neural core circuit to incoming axons in the same functional neural core circuit. In another embodiment, zero or more sets of connectivity neural core circuits interconnect outgoing and incoming axons in a functional neural core circuit to incoming and outgoing axons in a different functional neural core circuit, respectively.
Abstract:
An event-driven neural network includes a plurality of interconnected core circuits is provided. Each core circuit includes an electronic synapse array has multiple digital synapses interconnecting a plurality of digital electronic neurons. A synapse interconnects an axon of a pre-synaptic neuron with a dendrite of a post-synaptic neuron. A neuron integrates input spikes and generates a spike event in response to the integrated input spikes exceeding a threshold. Each core circuit also has a scheduler that receives a spike event and delivers the spike event to a selected axon in the synapse array based on a schedule for deterministic event delivery.
Abstract:
A method for object visualization includes providing an operator with an object filter tool through a graphical user interface, the tool comprising a rail having a number of shapes placed at distances from each other along the rail, the shapes representing divisions within a list of objects, distances between the shapes correlating to a number of objects between the divisions. The method further includes receiving from the operator, an interaction with the tool indicating a selection of objects within the list and presenting to the operator, a list of objects filtered based on the interaction with the filter tool.
Abstract:
An embolic protection device is provided for deployment within a body vessel to collect embolic debris there from. The device includes a filter for collecting the embolic debris and a frame for supporting the filter. The frame generally defines a closed loop that has a collapsed state and an opened state. Furthermore, the frame includes a tube portion that receives an opening means to open the closed loop from the collapsed state to the opened state.
Abstract:
Embodiments of the present invention provide a neural module comprising a multilevel hierarchical structure of neural compartments. Each neural compartment is interconnected to one or more neural compartments of a previous level and a next hierarchical level in the hierarchical structure. Each neural compartment integrates spike signals from interconnected neural compartments of a previous hierarchical level, generates a spike signal in response to the integrated spike signals reaching a threshold of said neural compartment, and delivers a generated spike signal to interconnected neural compartments of a next hierarchical level. Each neural compartment is further interconnected to one or more external spiking systems, such that said neural compartment integrates spike signals from interconnected external spiking systems, and delivers a generated spike signal to interconnected external spiking systems. The neural compartments of a neural module include one soma compartment and a plurality of dendrite compartments. Each neural compartment is excitatory or inhibitory.
Abstract:
The present invention relates to unsupervised, supervised and reinforced learning via spiking computation. The neural network 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 edges interconnects the plurality of neural modules. Each edge interconnects a first neural module to a second neural module, and each edge comprises a weighted synaptic connection between every neuron in the first neural module and a corresponding neuron in the second neural module.