摘要:
This disclosure relates generally to resistive memory systems. The resistive memory systems may be utilized to implement neuro-inspired learning algorithms with full parallelism. In one embodiment, a resistive memory system includes a cross point resistive network and switchable paths. The cross point resistive network includes variable resistive elements and conductive lines. The conductive lines are coupled to the variable resistive elements such that the conductive lines and the variable resistive elements form the cross point resistive network. The switchable paths are connected to the conductive lines so that the switchable paths are operable to selectively interconnect groups of the conductive lines such that subsets of the variable resistive elements each provide a combined variable conductance. With multiple resistive elements in the subsets, process variations in the conductances of the resistive elements average out. As such, learning algorithms may be implemented with greater precision using the cross point resistive network.
摘要:
This disclosure relates generally to resistive memory systems. The resistive memory systems may be utilized to implement neuro-inspired learning algorithms with full parallelism. In one embodiment, a resistive memory system includes a cross point resistive network and switchable paths. The cross point resistive network includes variable resistive elements and conductive lines. The conductive lines are coupled to the variable resistive elements such that the conductive lines and the variable resistive elements form the cross point resistive network. The switchable paths are connected to the conductive lines so that the switchable paths are operable to selectively interconnect groups of the conductive lines such that subsets of the variable resistive elements each provide a combined variable conductance. With multiple resistive elements in the subsets, process variations in the conductances of the resistive elements average out. As such, learning algorithms may be implemented with greater precision using the cross point resistive network.
摘要:
Neuromorphic computational circuitry is disclosed that includes a cross point resistive network and line control circuitry. The cross point resistive network includes variable resistive units. One set of the variable resistive units is configured to generate a correction line current on a conductive line while other sets of the variable resistive units generate resultant line currents on other conductive lines. The line control circuitry is configured to receive the line currents from the conductive lines and generate digital vector values. Each of the digital vector values is provided in accordance with a difference between the current level of a corresponding resultant line current and a current level of the correction line current. In this manner, the digital vector values are corrected by the current level of the correction line current in order to reduce errors resulting from finite on to off conductance state ratios.
摘要:
Neuromorphic computational circuitry is disclosed that includes a cross point resistive network and line control circuitry. The cross point resistive network includes variable resistive units. One set of the variable resistive units is configured to generate a correction line current on a conductive line while other sets of the variable resistive units generate resultant line currents on other conductive lines. The line control circuitry is configured to receive the line currents from the conductive lines and generate digital vector values. Each of the digital vector values is provided in accordance with a difference between the current level of a corresponding resultant line current and a current level of the correction line current. In this manner, the digital vector values are corrected by the current level of the correction line current in order to reduce errors resulting from finite on to off conductance state ratios.
摘要:
A robust and accurate binary neural network, referred to as RA-BNN, is provided to simultaneously defend against adversarial noise injection and improve accuracy. Recently developed adversarial weight attack, a.k.a. bit-flip attack (BFA), has shown enormous success in compromising deep neural network (DNN) performance with an extremely small amount of model parameter perturbation. To defend against this threat, embodiments of RA-BNN adopt a complete binary neural network (BNN) to significantly improve DNN model robustness (defined as the number of bit-flips required to degrade the accuracy to as low as a random guess). To improve clean inference accuracy, a novel and efficient two-stage network growing method is proposed and referred to as early growth. Early growth selectively grows the channel size of each BNN layer based on channel-wise binary masks training with Gumbel-Sigmoid function. Apart from recovering the inference accuracy, the RA-BNN after growing also shows significantly higher resistance to BFA.
摘要:
A method for transmitting data over a SL data channel wherein a transmit UE and a receive UE are each semi-statically provided with a CG configuration such that a CG configuration indication does not have to be transmitted in association with each individual data transmission during a duration that the CG configuration is applied.
摘要:
Methods and systems are provided for signaling for semi-static configuration in grant free uplink transmissions. Radio resource control (RRC) signaling is used to provide information from a base station to a user equipment (UE) that configure the grant free transmission resource to be used by the UE. In some implementations, the RRC signaling may be used in conjunction with system information that is transmitted to all UEs and/or Downlink Control Information (DCI) that the UE needs to access subsequent to the RRC signaling. In some implementations, the DCI includes an activation or deactivation indicator that the UE monitors to determine when the UE is allowed to transmit to the BS or should stop transmitting. Implementations allow for grant free transmission resources to be configured on an individual user based and a group basis.
摘要:
A user equipment (UE) receives a message that indicates a sidelink (SL) communication resource configuration to be used by the UE for communicating SL control information and SL data between the UE and another UE. The UE transmits SL control information according to the SL communication resource configuration, and transmits SL data according to the SL communication resource configuration. The SL control information and the SL data are transmitted by the UE without the UE receiving, in a downlink control information (DCI), a grant of communication resources.
摘要:
There may be situations in which it is beneficial for a user equipment to switch between grant-free uplink wireless transmissions and grant-based uplink wireless transmissions. Systems and methods are disclosed that help facilitate grant-based and grant-free uplink wireless communications, and the switching between the two. For example, systems and methods for mitigating collision between a granted uplink wireless transmission and a grant-free uplink wireless transmission are disclosed herein.
摘要:
Systems and methods are disclosed for performing hybrid automatic repeat request (HARQ) for grant-free uplink transmissions. Some of the systems and methods disclosed herein may address problems such as how to perform acknowledgement (ACK) and/or negative acknowledgement (NACK), how to determine and signal retransmission timing, how to determine the transmission/retransmission attempt and the redundancy version (RV), and/or how to perform the HARQ combining.