Abstract:
An apparatus includes a hardware sensor array including a plurality of pixels arranged along at least a first dimension and a second dimension of the array, each of the pixels capable of generating a sensor reading. A hardware scanning window array includes a plurality of storage elements arranged along at least a first dimension and a second dimension of the hardware scanning window array, each of the storage elements capable of storing a pixel value based on one or more sensor readings. Peripheral circuitry for systematically transfers pixel values, based on sensor readings, into the hardware scanning window array, to cause different windows of pixel values to be stored in the hardware scanning window array at different times. Control logic coupled to the hardware sensor array, the hardware scanning window array, and the peripheral circuitry, provides control signals to the peripheral circuitry to control the transfer of pixel values.
Abstract:
Methods and apparatus are provided for determining synapses in an artificial nervous system based on connectivity patterns. One example method generally includes determining, for an artificial neuron, an event has occurred; based on the event, determining one or more synapses with other artificial neurons based on a connectivity pattern associated with the artificial neuron; and applying a spike from the artificial neuron to the other artificial neurons based on the determined synapses. In this manner, the connectivity patterns (or parameters for determining such patterns) for particular neuron types, rather than the connectivity itself, may be stored. Using the stored information, synapses may be computed on the fly, thereby reducing memory consumption and increasing memory bandwidth. This also saves time during artificial nervous system updates.
Abstract:
A method of interfacing an event based processing system with a frame based processing system is presented. The method includes converting multiple events into a frame. The events may be generated from an event sensor. The method also includes inputting the frame into the frame based processing system.
Abstract:
A method for computing a spatial Fourier transform for an event-based system includes receiving an asynchronous event output stream including one or more events from a sensor. The method further includes computing a discrete Fourier transform (DFT) matrix based on dimensions of the sensor. The method also includes computing an output based on the DFT matrix and applying the output to an event processor.
Abstract:
A method of event-based down sampling includes receiving multiple sensor events corresponding to addresses and time stamps. The method further includes spatially down sampling the addresses based on the time stamps and the addresses. The method may also include updating a pixel value for each of the multiple sensor events based on the down sampling.
Abstract:
A method for transmitting values in a neural network includes obtaining a parameter value. The method also includes encoding the parameter value based on at least one value used by a neuron. The encoding is based on a spike to be transmitted via a spike channel.
Abstract:
Aspects of the present disclosure relate to methods and apparatus for training an artificial nervous system. According to certain aspects, timing of spikes of an artificial neuron during a training iteration are recorded, the spikes of the artificial neuron are replayed according to the recorded timing, during a subsequent training iteration, and parameters associated with the artificial neuron are updated based, at least in part, on the subsequent training iteration.
Abstract:
Methods and apparatus are provided for using a breakpoint determination unit to examine an artificial nervous system. One example method generally includes operating at least a portion of the artificial nervous system; using the breakpoint determination unit to detect that a condition exists based at least in part on monitoring one or more components in the artificial nervous system; and at least one of suspending, examining, modifying, or flagging the operation of the at least the portion of the artificial nervous system, based at least in part on the detection.
Abstract:
Methods, systems, computer-readable media, and apparatuses for image processing and utilization are presented. In some embodiments, an image containing at a face of a user may be obtained using a mobile device. An orientation of the face of the user within the image may be determined using the mobile device. The orientation of the face of the user may be determined using multiple stages: (a) a rotation stage for controlling a rotation applied to a portion of the image, to generate a portion of rotated image, and (b) an orientation stage for controlling an orientation applied to orientation-specific feature detection performed on the portion of rotated image. The determined orientation of the face of the user may be utilized as a control input to modify a display rotation of the mobile device.
Abstract:
Methods and apparatus are provided for implementing delays in an artificial nervous system. Synaptic and/or axonal delays between a post-synaptic artificial neuron and one or more pre-synaptic artificial neurons may be accounted for at the post-synaptic artificial neuron. One example method for managing delay between neurons in an artificial nervous system generally includes receiving, at a post-synaptic artificial neuron, input current values from one or more pre-synaptic artificial neurons; accounting for delays between the one or more pre-synaptic artificial neurons and the post-synaptic artificial neuron at the post-synaptic artificial neuron; and determining a state of the post-synaptic artificial neuron based at least in part on at least a portion of the input current values, according to the accounting.