Results 61 to 70 of about 192,666 (197)
MATEC Web of Conferences, 2018 The control performance of boost converter suffers from the variations of important component parameters, such as inductance and capacitance. In this paper, an online inductance and capacitance identification based on variable forgetting factor recursive
Chen Chen +5 more
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IEEE Access, 2021 The lithium-ion batteries of an electric vehicle belong to a high-voltage direct-current system. The high-voltage insulation performance of electric vehicles is very important for their safe operation.
Zhenbin Chen +5 more
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Kernel RLS Algorithm Using Variable Forgetting Factor
The Journal of Korean Institute of Communications and Information Sciences, 2015 In a recent work, kernel recursive least-squares tracker (KRLS-T) algorithm has been proposed. It is capable of tracking in non-stationary environments using a forgetting mechanism built on a Bayesian framework. The forgetting mechanism in KRLS-T is implemented by a fixed forgetting factor.
Jun-Seok Lim, Yong-Guk Pyeon
openaire +2 more sources
Pseudorehearsal in value function approximation
, 2017 Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole ...
A Robins +16 more
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Implementation of the Least-Squares Lattice with Order and Forgetting Factor Estimation for FPGA
EURASIP Journal on Advances in Signal Processing, 2008 A high performance RLS lattice filter with the estimation of an unknown order and forgetting factor of identified system was developed and implemented as a PCORE coprocessor for Xilinx EDK.
Jiri Kadlec, Milan Tichy, Zdenek Pohl
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Energies, 2018 The model parameters of the lithium-ion battery are of great importance to model-based battery state estimation methods. The fact that parameters change in different rates with operation temperature, state of charge (SOC), state of health (SOH) and other
Bizhong Xia +8 more
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Mechanisms of memory retrieval in slow-wave sleep : memory retrieval in slow-wave sleep [PDF]
, 2017 Study Objectives: Memories are strengthened during sleep. The benefits of sleep for memory can be enhanced by re-exposing the sleeping brain to auditory cues; a technique known as targeted memory reactivation (TMR).
Cairney, Scott A. +3 more
core +3 more sources
Retrieval-induced forgetting as motivated cognition [PDF]
, 2018 Recalling information from a particular category can reduce one's memory capability for related, non-retrieved information. This is known as the retrieval-induced forgetting effect (RIF; Anderson et al., 1994). The present paper reviews studies that show
Chernikova, Marina +4 more
core +3 more sources
Iterative learning consistency control for multi-agent systems with forgetting factors under random actuator failures [PDF]
Proceedings of the Estonian Academy of SciencesFor the discrete linear multi-agent systems with random actuator faults and system disturbances, an iterative learning control strategy with the forgetting factor is proposed. Firstly, the random variation of actuator faults with the number of iterations
Yuhan Li, Xingjian Fu
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Alzheimer’s Research & Therapy, 2021 Background Accelerated long-term forgetting has been identified in preclinical Alzheimer’s disease (AD) and is attributed to a selective impairment of memory consolidation in which the hippocampus plays a key role.
Jianwei Yang +11 more
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