Abstract:
A method and apparatus are provided to manage the assignment transmission resource of forward and reserve link that is assigned to transmitting entity for a period of time. An indication of a gap is provided whenever the transmitting entity is not transmitting actual data packets (e.g. whole or part of intended data or content), yet the transmitting entity is to maintain the assignment of the allocated resource. For example, an erasure signature packet comprising a first data pattern is transmitted on the assigned resource when there is no actual data to transmit on the assigned resource.
Abstract:
In one embodiment, a method of simulating an operation of an artificial neural network on a binary neural network processor includes receiving a binary input vector for a layer including a probabilistic binary weight matrix and performing vector-matrix multiplication of the input vector with the probabilistic binary weight matrix, wherein the multiplication results are modified by simulated binary-neural-processing hardware noise, to generate a binary output vector, where the simulation is performed in the forward pass of a training algorithm for a neural network model for the binary-neural-processing hardware.
Abstract:
In one embodiment, an electronic device includes a compute-in-memory (CIM) array that includes a plurality of columns. Each column includes a plurality of CIM cells connected to a corresponding read bitline, a plurality of offset cells configured to provide a programmable offset value for the column, and an analog-to-digital converter (ADC) having the corresponding bitline as a first input and configured to receive the programmable offset value. Each CIM cell is configured to store a corresponding weight.
Abstract:
Disclosed is an apparatus and method for classifying a motion state of a mobile device comprising: determining a first motion state associated with a highest probability value and with a first confidence level greater than a first threshold; entering the first motion state; while the first motion state is active, determining a second motion state associated with a highest probability value and with a second confidence level greater than the first threshold, the second motion state being different from the first motion state; determining whether the second motion state is to be entered; and in response to determining that the second motion state is to be entered, entering the second motion state.
Abstract:
Systems, methods, and devices of the various embodiments enable local visual identification and verification of robotic vehicles. Various embodiments may enable disambiguation of a robotic vehicle from among a plurality of robotic vehicles.
Abstract:
Various embodiments include methods for managing antennas on an aerial robotic vehicle used for wireless communications. A processor may receive position information identifying a location of the aerial robotic vehicle, determine whether to switch from using a first antenna to using a second antenna for active communications of the aerial robotic vehicle based on the position information, and switch active communications from using the first antenna to using the second antenna in response to determining that active communications of the aerial robotic vehicle should switch from using the first antenna to using the second antenna. The processor may make the determination using information from a database, which may correlate aerial robotic vehicle position to whether to use a particular one of the first and second antennas for active communications. The determination may also be based on a comparison of signal qualities obtained by both antennas.
Abstract:
A method of performing context inference is described. The method includes collecting ambient light at a spectrometer sensor integrated in a portable device, characterizing the collected light to obtain optical information, comparing the optical information to optical data predetermined to match one or more contexts, inferring at least one characteristic of a specific context based on the comparison, and determining a probability that the portable device is in the specific context.
Abstract:
Systems and methods for providing application-controlled, power-efficient context (state) classification are described herein. An apparatus for performing context classification with adjustable granularity as described herein includes a classifier controller configured to receive a request for a context classification and a granularity input associated with the request; and a context classifier communicatively coupled to the classifier controller and configured to receive the request and the granularity input from the classifier controller, to select a resource usage level for the context classification based on the granularity input, wherein a granularity input indicating a higher granularity level is associated with a higher resource usage level and a granularity input indicating a lower granularity level is associated with a lower resource usage level, and to perform the context classification at the selected resource usage level.
Abstract:
System and methods for performing context inference in a computing device are disclosed. In one embodiment, a method of performing context inference includes: determining, at a computing device, a first context class using context-related data from at least one data source associated with a mobile device; and determining, at the mobile device, a fusion class based on the first context class, the fusion class being associated with at least one characteristic that is common to the first context class and a second context class that is different from the first context class.
Abstract:
A method of performing context inference is described. The method includes collecting ambient light at a spectrometer sensor integrated in a portable device, characterizing the collected light to obtain optical information, comparing the optical information to optical data predetermined to match one or more contexts, inferring at least one characteristic of a specific context based on the comparison, and determining a probability that the portable device is in the specific context.